Synchronicity and patience –notice the surprises around you ?

Patience, we are told is a virtue, but it’s also a sign of power. Patience and strategy have a lot in common. In particular, both enable systemic change with their staying power and superpower of noticing. At least that’s what the strategy discussion group realized on Friday, June 29, and I later noticed connected to George Floyd’s predictable surprise murder on June 25.

Living with uncertainty is exhausting and when surprises strain our emotions, logic takes a back seat, and patience is crushed. A Strategy can serve as an insurance policy, as it prepares the mind and the organization for the possibilities and turns surprises into Something else. Aided by a few reference articles (posted below), let me explain.

2020 Surprises

All across America, crossroads of cities and towns of every size spontaneously draw protestors whose patience has expired. The people participating choose to convert their staying power into collective action, raise their voices, and use their presence to make up for their past silence. The seeming reactionary calls for change have erupted spontaneously and persisted for the past two weeks. This historic precedence for social unrest in the US has also inspired unity with people all across the globe.

Remembering George Floyd-#Black Lives Matter

After Memorial Day, expectations were shifting as more states lifted restrictions imposed to protect public health from the Pandemic. The focus for many focused on resuming freedoms of movement and engage in social activities. That Friday the strategy zoom discussion also focused on business and took up the topic “Creating synchronicity with patience”– how using coincidentally connected data could be a strategic advantage.

Our discussion prep references inserted unusual ideas–patience, and an alliterative list of considerations that tease out subtlety in connected data–Serendipity, Seriality, Simulpathityand Synchronicity.

By Saturday, my thoughts from the discussion still simmering, a series of conversations led me to play out the connected data associations concerning the death of George Floyd. The story had even been brought up at my synagogue virtual service. By nightfall, I realized the scenario and circumstances of his death were making the story increasingly big and horrible. Friday’s discussion helped me understand it was predictable.

Becoming Aware, Noticing

When notification of imposed curfew popped up on my mobile phone, I was taken by surprise. Outside, the usually busy intersection was quiet, and the city glowed. My response was tepid, dismissive. I attached meaning without thinking. The curfew was a mere continuation or renewal of ongoing public safety measures associated with the pandemic.

That’s just it, surprises by nature occur suddenly, catching us unaware, and the absence of warning triggers a response which may or may not demand our full attention. I didn’t notice what I had missed.

The next morning my understanding and thoughts shifted. A friend called to see if I was all right. Puzzled, I still appreciated her concern.

“Why wouldn’t I be?” I asked. She then called my attention to the news of protest marches and subsequent looting that had happened within a mile of my home.

I’m going out on a limb here, but I’d like to suggest that one way we make meaning of a surprise is we notice features’ coincident with other events. Or as the Psychiatrist Bernard Beitman explains, we must notice surprises in order to interpret their coincidence. He complied the following:

Horace Walpole called non-causal coincident surprises Serendipity. Paul Kammerer focused on their recurrence to define Seriality. Carl Jung observed surprising thoughts moving together in time and coined the notion of Synchronicity. Beitman himself followed with Simulpathity–simultaneous experience at a distance by one person of another person’s distress.

First class Noticers

The connections we make, affect our understanding, attach different meanings, open options, and decision points. Unlike automatic non-cognitive responses, strategic thinking and organizational planning prove powerful when connections made are deliberate, non-reactive. Max H Bazerman, the author of The Power of Noticing describes those who hold this power “first class noticers.”

As mentioned previously, noticing is complicated. Our attention is a protected internal resource that relies on our brain’s complex, highly selective and integrated assessment, and evaluation processes. Multi-tasking is a misnomer, the brain capably switches tasks faster than our ability to perceive a change of focus.

Similarly, organizations use structure, reward, and information systems to notice, enable but also contain and restrict connections in the name of preserving efficiency and effectiveness.

Traditionally, in science and business, practitioners utilize logic in the form of connected causality. Few tolerate or leverage coincidence in any form, especially as their focus favors higher frequency repetitions that further efficiency, and cost-effective scale.

Have you noticed the costs associated with efficiency? For example, short cuts, like habits we believe save time and energy, Their convenience frees our attention for other opportunities. But short cuts draw our attention and narrow our wider situational view, cutting out available data which in turn limits our further understanding. Habits are worse. Their formation in people or organizations reduces flexibility, range of response, and capacity to adapt.

Likewise, change proves difficult for individuals and/or organizations to effect or sustain because habits like social norms and culture prove resilient. They also render patience impractical.

Patience, Jonathan Black echoed in a piece for the Financial Times in 2019, “suggests passivity, forbearance, tolerance and even resignation. None of which are prized in the working world.”

First Class noticers in the form of Behavioral Scientists, User experience specialists and Design thinkers I suggest do recognize opportunities. They use research to seek out Serendipity, Seriality, Synchronicity and even Simulpathity.

They are less surprised by Black Swans, events whose timing is unpredictable and/or unforeseen has low probability of occurring none the less it remains known.

Max Bazerman calls these threatening events Predictable surprises. They represent serious problems that exist, won’t solve themselves, likely to get worse, and thus they become major crises. “Predictable surprises are a unique and significant consequence of the failure to notice important information and the failure to lead based on what you notice.” (p. 170 the power of noticing).

Behavioral Economists familiar with indecision have identified multiple human biases, of which not noticing is the default behavior.

Complex problems take time to sort out, and also a great deal of patience on the part of leaders as well as those assigned to address difficult tasks. Both leaders and problem solvers, Bazerman found sustain their success by learning and practicing behaviors of First-class noticers, a skill the writer Saul Bellow ascribes to someone who is also a seeker and searcher.

Though similar, only the most attentive notice their different intention. That which you seek, may or may not coincide with the location of your search. For example, someone experienced in making connections others might miss often help solve a problem in which the cause and effect are unclear, or unknown. Sherlock Holmes noticed the dog that didn’t bark.

The present era rewards businesses that prove themselves capable of delivering feedback instantly, conveniently makes impatience the norm. Every change surprises and though they appear agile adaptation proves difficult.

At Facebook, engineering teams prized for their agility were accustomed to working within arm’s length. Forced to work from home they struggled to adapt their communications behaviors. Other digitally born firms, who focused on establishing effective work processes also noticed additional value that operating differently makes possible.

BaseCamp, co-founder, CEO Jason Fried knew that effective coding required periods of deep concentration. His incremental experiments with workflow in parallel with improved interaction also freed employees to work remotely prior to the Pandemic. See his book on Remote Work.

Persistent patterns and growing trends threatening the black community were evident long before George Floyd’s murder in the custody of the Minneapolis Police. These first class-noticers recognized seriality in the data. They used Trayvon Martin’s murder in 2014 as an opportunity to raise awareness globally. Seizing power using affirmation they established Black Lives Matter . The surprise outpouring of protest was possible becasue BLM and others were ready for that predicatble Surprise.

The movement sustained itself using the tools and practices deployed by first class noticers to upend the complacency and excuses of coincidence to illuminate the systematic obstacles at work.

Strategic TakeAways

I had not missed news of George Floyd’s death on May 25 when the strategy discussion met on Friday the 29th, but I was not alone in failing to notice it’s significance. It’s only in reviewing notes of the group’s conversation that I see the connected takeaways.

1. The presence of data that may seem extraneous to your task, or focal range doesn’t make it irrelevant. If anything, the ability to connect independent data points depends on your ability to notice.
2. The Four S words remind us of opportunity in coincidence. Making time to scan the headlines and engage with people outside your expertise increases your exposure and opportunity to make meaningful connections.
3. Tactical assessments often require urgency and prove easier when patience is exercised in the development of strategic plans. The patience to imagine, notice, nd consider coincident events in advance.
4. The Pandemic forced everyone to change their routine. It made us more aware, sensitive to differences, broadened our understanding of doable options,and pushed us to adjust our expectations and priorities. it may help us redefine success to embody resilience, perseverance and incremental wins.
5. Patience is an interconnected skill and strategic tool effectively utilized by strong leaders. Its exercise manifests in time to observe, collect data, and think through the second, and third-order effects.

The unprecedented events of the pandemic and subsequent sustained protests following George Floyd’s murder make clear we are all part of a grander social experiment.

Convenience and instant feedback mark the digital experience. They push out patient behavior, which ironically is critical to our ability to notice and interconnect independent events, ideas etc.

Next time you are surprised, take the time to see what else you may have missed. Perhaps you will uncover additional strategic insights or opportunities.

ARTICLES Financial Times, Why Patience is a workplace virtue https://www.ft.com/content/230594d6-8eca-11e9-b8cb-26a9caa9d67b   Short Evolution from Serendipity to Synchronicity https://coincider.com/about-coincidences/history/ Overview of Research Design, DataCollection and Sampling https://youtu.be/WY9j_t570LY OPTIONAL Field Experiments in Strategy https://www0.gsb.columbia.edu/mygsb/faculty/research/pubfiles/6364/Field

Why research will remain a human activity

The future of business research– thoughts among peers 

Last Friday, July 20, I convened my monthly ad-hoc gathering of diverse professionals to talk about strategy. This month’s topic was the business of research and its future. As is our customary practice, participants reviewed in advance a series of articles to focus on and spur their thinking on the topic.

As moderator and convener, I’m always eager for a thought booster, and the conversation never disappoints me and to my delight, the participants find their time well spent. Opportunities to think aloud and have my own thinking challenged makes up for my time and effort to share selected articles, invite and then engage participants to deliberate on any topic.

Did my own thoughts on the future of research shift today? The answer is yes.  It’s challenging to do justice to a broad topic in 75-90 minutes, and still, we tapped several of the critical themes.

My synopsis follows of key thoughts I had neither considered prior—what motivations beyond curiosity generate research, and the approach affects and ultimate effects the future of research.  Note, participants occasionally chose to distinguish references to general terms by referencing the term via its first capital letter.

Beyond curiosity

I don’t expect people to stop being curious, and to my surprise, others pushed back on that premise. The growing conveniences mobile technologies’ afford to make new knowledge easy to access. The change in human behaviors and growing dependence they produce create efficiencies that limit or encourage us to forego active direct observation and discovery efforts. The changes may or may not affect the inspiration for further research or press the distinctions between general theory and accepted principles and specific cases that currently drives research.

The general conversation began by unpacking the presumption that research is a human activity inspired by curiosity.  Machines may accelerate, assist or be a subject of research but they don’t initiate research by themselves.

Big R-Research as a broad concept historically lays out a path to build knowledge.  Its value grows as the research is shared— its methods, raw input and the means that produce synthesis and transform the raw inputs into findings.

Sadly, the current state of the world reflects dilution of the term research and makes its application indistinguishable across a range of activities. Automated data systems generate volumes of research for consumption by both people and machines. The meaningfulness of findings now synonymous with results spit out all too often as visualizations—the new euphemism for graphical depictions of data.  Research results when they appear only in this form builds little actual knowledge. The capture of the latest observation and its addition to a trend line or as a portion of a whole does little to explain the how or why, fails on its face to challenge, enhance or enrich the general or standing understanding.

Alternatively, pure research falls into the Big R-research category that follows an open exploratory, investigative, discovery path. Commercial research can follow a similar path but its focus and test of determination must satisfy specified objectives determined to support, grow the business. Google Search team’s research development fits this latter category.

Even Google’s moonshot too because at the end of the day all the development and proceeds are owned and controlled by a commercial entity/patron. Any patents or new methods that result in these environments are not contributing to general knowledge but benefit the owners. Corporate research labs offer research academics environments flush in resources and data, but limit and control the distribution of their findings.

Sponsored business research appears to have a little more flexibility around its distribution and we discussed the benefits of two distinctive forms.

1. 1. Privately sponsored research by VCs, Google, or historically Bell labs whose activities often followed the lines of pure research contributed academic papers but not everything was published—needs verification.

A journalist asked Thomas Edison: “How does it feel to have failed 9,999 times.” Edison said, “I haven’t failed, I have had great success, finding 9,999 ways that do not work.”

The strategic meaning of this message?  Rather than share the failings, Edison preserved competitive advantage by holding onto 100 percent of his learnings from failure. Which is akin to the slow progress being made in pharma and other industries who seek to gain and preserve a competitive advantage, for the sake of slowing advanced development.

No one had an example of an industry who plays differently.

2. Government or foundation sponsored research manages to overcome some of these obstacles.  The coffers of US basic research advances general knowledge in multiple sectors, and again its use may hold some restrictions—the details need nailing down. Still government initiatives fund numerous advances in technology and other fields that both support the creation and ongoing survival of multiple businesses. For example, DARPA sponsored several Self-driving car competitions, Star Wars project by the Reagan administration work helped grow GPS capabilities, and NASA, who can forget TANG. Recent investments by the Chinese government seeks to create national strategic advantages over other countries and grow its domestic capabilities both human and technical.

These descriptions of research variations resemble geologic strata—where basic research or foundation research is the common denominator and each layer of specialization distinguishes and separates from subsequent layers while denying the integration. Perhaps the layers reflect the barriers of ownership that limit the spread of research and its findings within or across sectors by turning it into a property.

THE APPROACH 

When I worked in banking, I learned that without risk there was no reward.  Risks associated with research naturally attach to its scale, scope, the degree of ambition, as well as the uncertainty of results. Planning and the approach an organization takes in its research activities can mitigate and help an organization strike an acceptable balance.

Curiosity clearly is not the only inspiration for research, as was mentioned purpose and Big V-vision plays a role.

As mentioned, sometimes businesses establish a research arm hopeful these investments’ preserve the growth or survival of the firm.  The time horizon, the presence of a vision or a clear picture of opportunity often determines leaders’ expectations as well as their approach to research.  Leadership focused on near-term growth requires sharp clear means to quantify and justify their investments. They are more likely to seek incremental improvements or small differences and advantages, both easier to sustain and convert the investments into value.

Striking the right balance depends on your ability to understand both the timing and quantification of overall market demand, as well as your competitor behavior –capacity and capability to take market share. Intel’s research investments guided by Moore’s law exemplify this approach.

Understanding your competition, the concern of strategy departments’ research activities also contributes to the quantification of risk. Operationalizing SWOT using research fits this approach.  Rather than a one-shot if played out continuously, each stage benefits from contributions from research which also fuels its progression. Here’s how that would work.

Internally, research can turn known business weaknesses when supported and developed into strengths. Additional research benefits from these new strengths to seize external opportunities and ideally knock out external threats. A variety of research activities contribute to the momentum of this W to S to O to T quashing cycle. Similar research activities afford discovery or wider awareness of emergent external Threats while also furthering self-recognition of corresponding internal weaknesses that create momentum for never-ending review and invest cycles.

Another approach I’ll call Comparative research reflects business leaders’ ongoing preoccupation to produce goods and/or services faster, better and/or cheaper. Note this approach resembles Deming and Toyota Production Systems focus on incrementalism and continuous improvements while also engaging and focusing internal attention to improve singular value measures.

A third approach mimics the scientific approach in which the research objectives are very narrowly drawn and success and failure clearly defined. In the digital environment, many teams engage in A/B testing of a change designed to enhance performance at very low levels but potentially lead to bigger results.

All three of these approaches are Evaluative—in that all produce measurable changes in value. The comparison of an idea’s value and its worth to the organization when measured justifies the research activity.  If the idea’s value can be assessed, then conversely, the risks of not developing or pursuing the idea are measurable too.

Efforts to achieve bigger R research that produces more ambitious results requires additional justifications. Their additional risk may reflect a wider set of leadership capabilities and strategic agendas. Venture capital hopes their investments turn into unicorn businesses rely heavily on research and analytic assessment capabilities.

The reliability and predictability of timetables to results slide in proportion to the size of the ambition to achieve Big R research characteristic of the unknown domains or even the unknown unknowns.  The greater the gap or risk reflects several things: one, the distance between what the organization knows and/or is knowable and what it doesn’t; two the extent of discovery needed; and three the level of organizational ambition.   [Note, this might reduce to the time value of money calculation, rather than a more elaborate justification for research as risk clearly factors into organizations decision, research and likely research activities. ]

The Big V-Value aspect 

Conceptually,  the discussants also recognized other aspects of research along with a different continuum that doesn’t lend easily to quantification.  That’s when research inspirations resemble discovery. Both relate to finding, becoming aware of something previously unknown to either the seeker or the wider world.

This is an experiential aspect, in which emotions and brain processes not fully understood play a critical role—this is what I’ll call the Big V-value aspect of research.

Philosophers focus on bigger questions that humans ponder and may be alone in their pursuit, but none the less persistent in their search. I  mention the eternal questioning that humans experience and undertake, such as:   “Why are we here? ” “What’s my purpose, what difference can /should I be making?”

The ideas, activities we value don’t always equate to a market value, or its economic utility and/or price.

It would be remiss to talk about research and its future without acknowledging that inspiration and deeper motivations drive our behaviors and often cause us to reverse direction. Here are a few examples of research revisiting the initial assumptions;

Two engineers now at Google –Asa Razkin and Tristan Harris, realized their efforts to improve and increase convenience on mobile devices also led to over-consumption. As a result, they gave rise to a revolution to return control to the users.

https://video-api.wsj.com/api-video/player/v3/iframe.html?guid=2D3A120C-C88F-4C81-A005-1439E464A507&shareDomain=null 

Similarly, the decision theorists and the behavioral economists who recognized that valuations were not the only consideration when people were facing economic decisions.  This has also given rise to designers recognizing that removing friction or simplifying a path prevented people from having to collect their thoughts before proceeding—thus removing barriers or friction was not always an optimal approach. To learn more about positive friction, I recommend this piece https://www.slideshare.net/secret/NPcI5mCnlpvYsR

It’s impossible to avoid the realization of research as circular versus the approach of increasing that we sense to trend linearly.

Would welcome your thoughts, or reactions!

ARTICLES that were previewed in advance follow:

1.What happens when data scientists and designers work together (~7-8 min read)
HBR March 2018
https://hbr.org/2018/03/what-happens-when-data-scientists-and-designers-work-together

2. Tom Peters True Confession (~20 min read)

FastCompany 2001
https://www.fastcompany.com/44077/tom-peterss-true-confessions

3. Google-X and the science of radical creativity (~40-50 min read)
The Atlantic, November 2017
https://www.theatlantic.com/magazine/archive/2017/11/x-google-moonshot-factory/540648/

Optional
4.Why is the insights startup community exploding? (4-5 min)
https://greenbookblog.org/2018/05/29/why-is-the-insights-startup-community-exploding/

5.How Disruptions are Born and How It Applies to the Market Research Discipline (7 min)
Greenbook June 2014
https://greenbookblog.org/2014/06/09/how-disruptions-are-born-and-how-it-applies-to-the-market-research-discipline/

6. 7-8 min)
https://medium.com/@workatplay/the-persona-is-past-its-prime-meet-the-mental-model-a41ac415906d

Brands and Politics, can the mix lead to healthy business growth?

Successful brands have always found influencers and celebrities helpful in selling their product. Sometimes brands embed messages hoping to ride the waves of cultural change all the way to the bank.  But when the winds change suddenly, how a brand navigates the wave impacts its survival. 

Is your strategy impeding or promoting adaptive change?

Change, it’s what most business executives recognize as a constant threat. Unfortunately, many find themselves between a rock and a hard place. How might managers ably meet tomorrow’s change in environmental conditions?

Rather than react, plans that consider structure and processes matter. So too does understanding their organization as an integrated and dynamic whole.

Factors that create efficiency and make an organization and its team effective today appear less stable all too quickly.  The growing connectivity and access to information affects the pace and scale of  technology developments, consumer expectations and competition.

An organization’s survival depends on its ability to adapt and respond to external changes in its environment as well as introduce changes internally.

The connections between strategy, structure and processes not only prove defining for many organizations but also the source of pain or promise to its survival.

Participants in the Strategy discussion took a look in July 2017 at a few articles (posted at the end)  that focused on decision-making challenges that make organizations struggle to adapt.  Here’s some of what we discussed.

Choosing when and what to Change

People adapt to expected change by planning. A strategy clarifies expectations making both planning and adapting to change easier. Strategy when well communicated and understood articulates the underlying purpose that drives an organizations’ leadership to make a change. Strategy in this sense, is a choice of action affects the quality and effectiveness of changes and degree the changes stick.

Management theory differs from strategy, though it too creates expectations that make planning and adapting to change possible.  Management theory determines the organizations’ structure and processes.

Not every change that occurs is expected, and not every expectation gets realized. Both situations require adaptation but few organizations prove capable consistently of decision-making that continuously holds their competitive advantage.

Why one business proves more resilient, and/or adaptive than others continues to elude the best managers and leaders. Cause and effects are complicated to identify let alone sort out.

Nearly fifty years ago,Raymond Miles, Charles Snow, Anal Meyer and Henry J. Coleman, Jr –four management academics set out to understand the process business use to adapt. They looked for patterns in order to prescribe how existing managers might successfully meet tomorrow’s or different environmental conditions.  Their framework remains relevant and informative because it encourages management to see their organization as integrated and dynamic wholes.

For a small, or start-up business this perspective mirrors the intensity of collective singular focus on survival. Once secured, the collective focus naturally diffuses. Accommodating growth each functional role establishes separate priorities that over time compete rather than integrate their resources.

In 1978, existing descriptions of organizations’ ability to adapt were lacking. The authors of Organizational, Strategy structure and process  used their Organizational Behavior and Industrial Relations backgrounds to inform and then describe three categories of processes: entrepreneurial, engineering and administrative.

Miles et al break down basic decision making for managers into three categories: administrative, engineering and entrepreneurial. Organizations’ top management limits their choices of adaptive behavior to those they believe allow them effective direction and control of human resources. They observed that whatever theory of management executives endorsed factor significantly in their subsequent analysis of organizations’ ability to adapt to changes in the environment.

Their preliminary research uncovered a series of patterns relating management theory and organizational strategy and structure.  Fifty years later, these relationships remain evident though more patterns and interpretations and management theories have emerged. Note, this article predates the work of Michael Porter’s industrial economics inspired descriptive five forces theory of Competitive Strategy.

The evolution of expectations between managers and employees are three components of the patterns based on

1.  a set of assumptions about human attitudes and behaviors,
2. managerial policies and actions consistent with these assumptions, and
3. expectations about employee performance if these policies and actions are implemented.

In light of the attention currently paid to organizational culture, their observations prove interesting, especially as nowhere in this article does the word even appear. That’s not to say they overlooked this concept. The authors merely draw the attention of management to individual behaviors and expectations with a prescriptive suggestion for their evolution from a traditional model to a human relations and a human resources model.

Perhaps culture issues playing out in many organizations reflect challenging dynamic patterns these authors identify as: Defenders, Analyzers, Prospectors and Reactors.

Here’s my crude descriptive summary

	Defenders	Analyzers	Prospectors	Reactors
Innovation	Low	Moderate	High	Low
Efficiency	High	moderate	low	low
Centralized Decision-making	High		Low
P&L autonomy	Low		High

As you can see, instead of finding a direct alignment between patterns of decision making associated with different management theories and the ability to adapt, the authors  found a mix of assumptions, policies and expectations.

Holding together a dominant coalition with mixed views concerning strategy and structure is not an easy task.

Miles et al found managers engaged in new product or service development struggled to function within planning, control and reward systems established for more stable operations.  Analyzer organizations must be successfully differentiated into its stable and changing areas and managed accordingly.  ….Numerous organizations either led or forced into a mixed strategy (multinational companies, certain forms of conglomerates, many organizations in high technology industries) and their struggles may well produce a new organizational type and demands for a supporting theory of management.

To meet tomorrow’s  environmental conditions successfully, manager’s must ably understand organizations as integrated and dynamic wholes.

A balance sheet view

I reached out to Shep Pryor, a Chicago Booth grad, co-author of The Private Equity Edge and faculty professor. I hoped his  fluency with company financial statements could  help reveal the presence of similar strategic choices about structure and process that Miles, et al described.

I asked him about examples in which the statements might reveal the effectiveness of a decision to enter a market or offer new products, and if they depends less on environmental conditions and more on strategic choices of internal structure and process?  At least that’s what my initial take on the prescriptive in the article.

Here’s Shep’s very cogent reply:

Whether a financial statement analysis, or perhaps a broader 10K, which adds additional content to the financial statements would enlighten the analyst on where the reporting company is in the spectrum described in the article.

First a comment on the article, and then maybe I can shed some light on an answer:

The article categorizes the adaptive capacity of companies more or less as follows:

	Low Flexibility	High Flexibility
High Stability	Defender	Analyzer
Low Stability	Reactor	Prospector

It goes further into its definition by stating that each company must bring some balance to bear on three main problems: entrepreneurial, engineering, and administrative. Finally, the authors point out that managerial theories (and their associated practices) held in high esteem by top management will enhance or confound the company’s ability to adapt.

The main points I [Shep] get from the article are:

1. Each of the first three types of adaptive behavior may lead to business success but only if the management team’s theories and practices enable them to keep the three fundamental problems (entrepreneurial, engineering, administrative) under control.
2. Being a Reactor is a default position for companies that lose their capability to maintain strength as one of the other types. Avoiding the position is crucial.
3. Changing from one box of the matrix to another is a perilous enterprise.

What their commentary brings to mind as good examples:

1. Ford motor is a Defender, but it is moving toward being a analyzer, as its market is invaded by different technology by such firms as Tesla.
2. Sears was a defender with no hope of transforming, so it has become a reactor, and will soon become a memory.
3. United was a Defender when Southwest was a Prospector. As the environment changed to favor Prospectors, Southwest gained dominance.
4. Kodak Defended its vanishing market to the death, that is, to its own death.

What can you learn from a 10K?

1. Defenders are likely to be company with higher levels of fixed assets. The more capital intensive a company is within its industry, the more operating leverage it has, and thus the more dependent it is on growth and stability. High sales can lead to colossal margins, while sales below breakeven cannibalize net worth. In the same industry, a company that is less capital intensive, will be able to maintain its margins despite variations in sales.
2. If the MD&A of the 10k dwells on a variety of new product introductions and a lot of small acquisitions, the company is probably a Prospector.
3. While companies are notorious for cloaking their true sectors in the 10k sector analysis, if there are disparate businesses highlighted in the sector analysis or the other commentary, it will be clear that the company is at least trying to be an Analyzer. For example, a successful company that makes truck axles and also sells ceremonial tea sets through a party plan is an Analyzer, while an unsuccessful company that does the same is a Reactor.

A little financial forensics can go a long way.

The Articles

Alignment of Strategies

http://smallbusiness.chron.com/alignment-strategies-4649.html

Organizational strategy, structure and process
The Academy of Management Review, July 1978

http://www.wiggo.com/mgmt8510/Readings/Readings5/miles1978amr.pdf

How aligned is your organization

https://hbr.org/2017/02/how-aligned-is-your-organization

OPTIONAL

If you need a focal point to think about the question, consider the activist investor LOEB’s stake in Nestle

Nestle: Third Point Daniel Loeb Activist Investor

https://nyti.ms/2tbczyS

What’s Up with Retail: Invention easier than Transformation

 

The business headlines have been full of news about store closings.  Multiple chains are closing 100s of stores.  This once flourishing sector employed thousands, and now flounders. What strategic lessons can be learned from US retailers mistakes? The question and the learning opportunities for other sectors became the basis of the April 21, strategy roundtable’s diverse group of attendees.  A few articles  offered some summary context of the state of the sector, a little history about Macy’s and a series of growth related insights from disruptive innovation strategy firm , published in MIT Sloan Review offered by Fahrenheit212.

Surprisingly, after posting the articles in late March, a flood of store closings and their back stories continue to appear, leaving many to wonder what’s up for several of the biggest brand names in retail.  In the short horizon that  Macy’s lost $10billion in value, Amazon rose $300bil to reach its current six year low of $6bn, considerably off its peak of $24bn in 2006, Amazon’s current valuation just north of $370bn continues to accumulate market share.

The US Big Box Retailer’s current state isn’t just bad luck and it turns out to be less than easy to pinpoint. As Macy’s and other retailers struggle to maintain a fresh look, their poor performance ripples across the sector as one domino topples over another. No excuse for Management to become such terrible shop keepers, no matter how much online competitors divert their attention.  A poorly appealing store worsens its merchandise and thin staffing ratios erode service combine to turn off customers too.

Sears posted year on year decline over 9 percent, and 1.5x losses for its mobile application as it’ digital transformation efforts prove insufficient.

Cost cutting may help a business survive, but won’t deliver growth that makes it thrive. The creative fuel behind the early growth of Sears, Macy’s and the general merchandisers also expanded their market and showed their competitive capabilities. Amazon isn’t a new disruption and the blanket of doom seems to spread uniformly across the sector.

The Data vs. the Narrative

Did you know from 1990 to 2014, US retail employment grew by 2.3 million, of which the vast majority was among non-store retailers?  The total sector grew by 17 percent, while non-store employment grew 27 percent. In this same period, a combination of productivity gains and drops in labor compensation reduced the sector’s unit costs.

These reversals in historic trends pointed out by  Chicago Booth faculty Chad Syverson and Ali Hortaçsu in their recent review of US retail, should help large retailer’s right? More part-time workers, more automation and lower wages do improve operating margins, but doesn’t mean growth will follow.

The bigger strategic problem is timing and the ability to compete. The efficiency gains across the sector appear just as retail’s share of total US economic activity continues to shrink, and correspondingly its share of total US employment diminishes too.

Syverson and Hortacsu found ample research that relates technology, management, variety and productivity with shaping the success and survival of some retailers.  Surprise, greater productivity may or may not result from any one of these factors, and growth from greater productivity seems less causal too. Physical operations, however do prove important to both e-commerce and store based retailers. In other words, the formula for growth has grown more complex. Hold these thoughts.

Many explanations of changes in the sector, they say, “ …build on two, powerful and not fully consistent narratives, a prediction that retail sales will migrate online and physical retail will be virtually extinguished, and a prediction that future shoppers will almost all be heading to giant physical stores like warehouse clubs and supercenters.”

Their extensive data review also makes clear that the data does not support these narratives.  Online retail supremacy has not yet arrived, and likewise the scale and influence of the supercenter/Warehouse merchandisers continue to grow.

“Between 2000 and 2014, the fraction of all retail sales accounted for by e-commerce has risen steadily from 0.9 to 6.4 percent…The increasing share reflects an 11-fold increase in nominal annual e-commerce sales, in contrast to a 55 percent increase in nominal retail sales as a whole.”

The latest (4Q2016) US Census reports total retail sales of goods and services at $1,235.5Billion and estimates ecommerce at $102.7Billion (8.3 percent of total). Year over Year growth rates of 4.1 overall were considerably lower than ecommerce, which grew by 14.3 percent. Both grew only 1.9 percent over 3Q2016.

The analysis by category over time and projection of the trend lines summarized below makes the story more interesting.

Syverson and Hortacu’s                                                 Projected year that product’s 

 Table I: Product-specific E-commerce                        share expected (purple achieved):  as a Share of Product Total Sales

The summary resembles an 80/20 analysis.  The categories with the biggest ecommerce sales represent the smallest category of total sales.

A Theory We tested

A recent edition of MIT Sloan Review published three “new” growth-related truths, and framed our discussion. The truths as you see, resonate with many of the common precepts around innovation focused strategy not just those of its authors from Fahrenheit212, part of Deloitte.

1. Analysis won’t reveal your way to the future, you must invent it.
2. Competition is not linear, it’s exponential and disruptive.
3. Success depends on internal capabilities to catalyze an organization into action, and make something new happen.

First, analysis has broadened in many ways, but its purpose and practice still largely  determined by Leadership and its management priorities.

Limiting the scope of Analysis to tactical issues, confirms what works, or drives larger strategic projections as in what’s possible. Today, analysis and analysts review data in every function across the entire enterprise. Organization benefit from analysis when they also  commit to standards of consistency and integration, that also assure their results don’t confuse but reveal factors important to business growth.

Successful analysis also relies on the availability of data and analysts capable of its interpretation. Today’s connected world offers ever increasing opportunities to collect, store and process more data cheaply, and Enterprise Resource Planning Software systems greatly simplify and automate the reporting of standard views of activities in every function.

Planning and Process Improvements both suffer from a shortage of analysts capable of integration and interpretation of big data within a business context. The standards for business reporting reinforce old habits, rely on established metrics and existing interpretations, and thus miss cross-functional opportunities to share findings and develop new insights.

Is perspective and Interpretation hard to come by, or just hard to hear?

For example, to reach $150 million in annual sales, took Walmart 12 years and 78 stores. From its inception in 1994, Amazon took only three years. Further, Bezos reported 1998 net income remained close to zero as he his continuous focus on growth tirelessly plowed cash back into business development.  Not only did Amazon’s sales success patterns defy conventions of growth metrics, their unconventional use of data, analysis supports their creative capabilities and discoveries to understand what was contributing to their growth and working for their customers too.

In 1999, Forrester Research reported annual web retail sales as a whole jumped from $700 million to $20 billion, though it remained less than 1% of total retail sales. Growth was anything but linear—but the base too small to catch the eye of established, experienced retailers.

In 2001, Border’s CEO Greg Josefowicz was a very experienced and sophisticated retailer and no stranger to Ecommerce having come from Peapod. The fractional contribution of the chain’s online sales however led him to outsource the channel to Amazon. This was the same year, that Apple released the iPod. Unless you were closer to online data, and keenly understood its opportunity to track customer journeys and gain behavioral insights, chances are you too would have overlooked the value of further investment.

source: https://www.altocloud.com/blog/online-buyer-behavior.-what-we-can-learn-from-traditional-buyer-behavior

A 2016 interview with Michael Edwards, interim CEO Borders from January 2010 through its bankruptcy and liquidation in July 2011 revealed something else. Edwards buys into Fahrenheit212 philosophy that little can prepare you for wholesale disruption.  2010 was a period of widespread economic growth and US retailers sales were growing, but not uniformly; and not if you were in the book and electronics industry (aka ESMOH)—again hold that thought.

“The pivotal moment for me is when Apple launched the iPad,” Edwards said. “That foundationally changed the (book) industry forever.”Essentially, the iPad was a Borders in your hand. It had books, music and video. And people had access to millions of books.”

These hindsight claims made me wonder why Border’s didn’t feel any sales fallout from the iPod or Apple earlier, or when and why they misread Borders’ customers  change in shopping patterns?

Is your analysis reporting monitoring activity or action oriented?

What analysis and shared insights did Borders leadership encourage? Were traditional metrics misdirecting their strategic priorities and explain how their widespread physical presence was suddenly without value?

Remember the dominant narrative that Syerson and Horascu found?

Put that thought together with the analysts’ tunnel vision driven by elaborate ERP systems that accurately report established growth metrics. Monitoring Same Store Sales, Sales by channel or category breakdowns do reveal changes in shopping patterns, but are they actionable?  Even the Ecommerce reports from outsource vendor Amazon likely to include detail level data and helpful comparisons.

Different stories and trends emerge when analysis incorporates outside reference points. Benchmarking internal data to publicly available government statistics, for example, not just aggregate retail sales vs ecommerce but within their category might have raised alarm bells early.  Time pressures and priorities don’t have to stop anyone from creating a look similar to  Syerson and Horascu cumulative look.

What are you using to define your market and meet the needs of your customer?

Rethinking how to deal with consumers is more than a marketing plan it’s a strategic imperative.

At least that’s what Mike Edwards realized when he stepped up from the role of Chief Marketing Officer to help turnaround Border’s in 2010.

Conventional analysis techniques and formats don’t address deeper questions that test the validity of your strategy, or draw attention to important indicators affecting your results.

If you are a big retailer, and you moved online, you have big data. Macy’s and Sears both moved somewhat early to create an online presence before 2001. Maybe they saw online as an efficiency improvement to catalog sales, they still kept them independent of ongoing business activities.

Perhaps their experience relied too heavily on mass-market demographic information that large vendors like IRI made easy to digest.  Capabilities to analyze the flood of big data and the detail byte size moves of website visitors exceeded the capabilities of the most nimble and agile of digitally born players.

In 1998, the year Google was released, Wired reported the evolving capability of a website to gain intimate knowledge of their visitors. Excite, the leading search engine at the time, collected 40 Gigabytes of data daily in its log files based on 28 million daily Page Views. They only tracked directional patterns, though “for the first time, the continuously updated empirical evidence needed to assess relationships and deliver better experiences was available.”

A gap emerged between traditional marketing training and opportunities the web’s detail user journey tracking revealed. Do you appeal to demographic and assembled personas, OR are you responding directly to individual users’ needs?  This gap mirrored the unfolding of a larger competitive divide across all businesses and  further segregate online activities into separate operating units.

Bigger organizations’ centrally controlled decision making contrasted sharply with the emergent capabilities of online technologies and few recognized the important tasks required to rethink how to deal with evolving learning by their consumers and suppliers.  No problem for Excite, the leading search engine in 2001 and Amazon.   “Any active data we get, [Joe Kraus, VP of Excite explained] we put to instant use on the page…simulating personalization such as zip-code based weather forecasts.” Amazon without knowing any personal information, began to pass on simple recommendations based on the cookie data.

Cookies track specific behavioral data online, that was difficult to connect to purchase and profits, but still offered considerable strategic insights to anyone who took the time to look. Ironically, only a handful of advertisers possessed the technical and marketing experience with this growing data, which meant the playing field for ably using the information to optimize profits was wide open. Instead of investing and experimenting, many continued to apply the store sales success criteria to online sales.

Narrative Backstories: Perspective colors perception

I’m no retailer, but I did learn a few things from my father who created a handful of custom drapery stores that flourished in the 50s and 60s only to succumb to changing demographics in the 70s.

• Purchasing frequency and customer loyalty aren’t accidental. Relationships build on more than serendipity.
• Knowing your customer earns trust, most evident when your recommendations produce sales. Note, this approach doesn’t depend on markdowns or price drops to attract interest or make a sale.
• Convenience is a perception not the reason passers-by cross the threshold (or click through).
• Locations with heavy traffic create greater opportunity, sure, creative storefront displays (content) arouse interest or curiosity, and sales follow when entering visitors rewarded positively.
• Invention matters but delivers greater value when balanced with conventional, basic goods and service options.

Drawing customers in, attractive presentation of merchandise has always helped successful merchants move what had to be moved. It’s been true for sellers regardless of their circumstance and environment.

Three longer term trends

Every trend has an origination point, successful analysts recognize the significance early because they often understand change as relative.  It’s easy to see the internet as a significant force today, but in the mid-1990s, analysis shown earlier documents  the case’s weaknesses and risks.

In 1995, Grace Mirabella, former editor of Vogue  broadens the context in her memoir In and Out of Vogue.  She describes dramatic shifts in the minds of consumers about department stores’ relevance compared to their hey day in the post-war period. 22 years later, her words don’t sound the least bit out of date.

“[B]efore malls and discount outlets and chain stores…[department stores] were the great halls of merchandise, and they provided an enormous variety of goods at much more varied prices than the present.  …each store aimed for a certain style, a certain specialty market, and a certain clientele, and you knew the minute that you walked into any one store, and smelled the perfume and saw the flowers and doormen or bargain tables, precisely where you were. “

Each family owned store’s attitudes and sensibilities she explains, accompanied the details that clued in customers, established unique contracts with manufacturers and made evident by the difference in merchandise they carried.  In the 1970s, Mirabella remarked on two major shifts:

• Designers became all-powerful, cutting deals that promoted their name, and reducing retailers into commodity distributors who all carried the same things.
• Consolidation by conglomerates followed.

“[The named department stores] started to take on the feel of the real estate ventures that they had become.  They lost their sense of purpose, of conviction.”[p. 45]

In 1994, Jeff Bezos, left his job as hedge fund manager for DE Shaw. Interviews reveal he spotted opportunity in the expanding internet, which led him to start the company he later names Amazon. His analysis skills suggest he was deeply familiar with another trend that began in the 1970s, one, that Mirabella in her backward look from her publishing perch misses–the evolution of Electronic Digital Interfaces (EDI) streamlining procurement.

In his first 1997 letter to shareholders, Bezos lays out his vision and writes:

“Today, online commerce saves customers money and precious time.  Tomorrow, through personalization, online commerce will accelerate the very process of discovery.  Amazon.com uses the Internet to create real value for its customers and, by doing so, hopes to create an enduring franchise, even in established and large markets.”

Personalization historically differentiated the high end of the market. Sales persons kept coveted black books that contained intimate notations about their customers ranging from size, color and style preferences to  special occasion dates and family details. Amazon wasn’t the first to collect user data, and was by no means able to mine it and yet they produced “personal recommendations” beginning in 1998 without investing in developing complex analysis capabilities. That came considerably later.

They took a shortcut that other websites  noticed satisfied customers. Chris Bayer writing about personalization for Wired in June 1998 explains it this way:

“The trick is to use technology to achieve the same economies that you have in a mass-marketing model, while delivering some personalized messages to the consumer,” says Rex Briggs of Millward Brown Interactive. A less visionary goal than one-to-one, surely, but far more realistic. It’s called mass customization, and if you can get past the oxymoronic bounce, you can see that its possibilities are not lost on the consumer-products retailers who have carved out a market for themselves on the World Wide Web.”

In 1999, Academics Joe Pine and James Gilmore publish The Experience Economy continues to shape many retailers strategic perceptions.  Their thesis builds on the retailer narrative and emotions Mirabella evokes, and connects to my own Dad’s experiences as a lifelong retailer.  Experience, they explain is now the metaphor of choice.  What else summarizes the combination of factors that attract and convert a visitor into a loyal, frequent customer and/or influencer?  Keeping  experiences relevant and meaningful amidst the backdrop of rapidly changing forces that impact every aspect of your business model demands rethinking of the employee not just the customer experience.

Direct learning

Unlike the leading CEO retailers failing, Bezos shares more in common with the great merchandisers of the past.  His digitally born and situated store front owes its business growth to continuous, bold experimentation as well as deep analysis. I don’t know what metrics are commonplace at Amazon, but their investments in data analysis capabilities and machine learning are self-evident by the efficiency and sideline cloud business they produced.

The speed in which consumers change their behaviors prove challenging for every retailer, non-store or store.  The online e-tailers’ unique environment, fully equipped to capture detailed user journey references and history can use the same mechanics to deliver immediate responses ranging from mass personalization to levels of deeper customization.

Amazon’s strategy embraces the principles of continuous learning at its core to control every aspect of the buyer’s experience. Similarly Apple, another company with astronomical market valuations entered the retail market in order to control and enhance the buyer’s experience.  Today, both have physical presence that emphasizes service and consumer education.

Retailers who miss the ability to construct a holistic strategy, increasingly are dying in the evolution of  responses or deeper customized, delivering valuable feedback enabling the business to continually improve its offerings and willingly take risks associated with invention. Amazon learned quickly how to draw customers online, present the merchandise attractively and yes move what had to be moved.  He didn’t have to balance the demands of managing existing outlets, nor accept established practices associated with large scale distribution networks, instead he invented his future.

In 20 years of online commerce, only a few companies strategy match Chris Bayer’s  observation that “”serious” companies are rethinking the ways they deal with consumers, and the idea of  mass customization ….using the trick of technology to deliver a personalized message that isn’t really personal at all.”

ARTICLES

Reframing Growth Strategy, Sloan MIT Review

http://sloanreview.mit.edu/article/reframing-growth-strategy-in-a-digital-economy/

Contrast in transition: Sears and Macy’s

https://centricdigital.com/blog/digital-strategy/how-sears-and-macys-are-transitioning-into-an-improved-digital-strategy/
Macy’s relationship trouble with Luxury brands

https://www.bloomberg.com/gadfly/articles/2016-08-11/macy-s-earnings-relationship-trouble-with-luxury-brands

Five Trends driving traditional retail towards extinction

https://www.forbes.com/sites/jjcolao/2012/12/13/five-trends-driving-traditional-retail-towards-extinction/#11487bd51efd

 

What Future does your Technology Strategy Make Possible ?

What’s consuming your time and energy these days?

What’s harder, coming up with a plan or the planning? Today, numerous automation technologies make modeling and planning easier and more widely accessible . In fact, automation is just one of the many values upgrading to digital technology tools offer.

This is not why, John Hagel of Deloitte,  notably suggests organizations should look ten, if not twenty years out when  when developing digital strategies. He found that of the 2% of companies who say their thinking makes use of  truly long term horizon, they derive considerable benefit.

Yes, I swapped the word thinking for planning to be truer to Hagel’s observations. Technology changes’ inescapable link to organizations’ Financial Performance  forces everyone to keep up, and that’s both good and bad, he recently told the MIT Sloan Management Review: 

“[Hagel’s] sense that the old approaches are just not sustainable, and some senior executives have seen the need for fundamental change driven by this technology. The big issue for them is how to get that change to happen in a large traditional organization.”

Wait, he’s not talking about scenario planning, a worthy tool in the strategic tool box that proved advantage to Royal Dutch Shell with lengthy timelines for oil discovery and extraction. This contrasts with Digital technologies timetables, stuff that changes faster than anyone has been able to imagine.

This short term focused impact thinking Hagel and others suggest proves self-limiting and injurious to organizations.Particularly because both changing culture and enabling learning are time intensive activities and rarely get priority, and arguably leads to performance failures in too many organizations.

Thinking through a technology change

Global Positioning systems (GPS) technology, for example, everyone now recognizes removes the pain and uncertainty of time, distance and routing. The tools also deliver greater efficiency and optimize resource utilization. In 1973, when the US launched its first GPS satellite project, few organizations began to imagine how geolocation capabilities  could enhance their business.

What did they have to understand? What were they waiting for? When did it become obvious and inevitable that Geolocation was an imperative in every business?  I imagine thinking through this change might go something like this.

Built in navigation tools became available in the first mobile phones and improvement has been continuous; however the new opportunities and new businesses they have created were described as disruptive. The number of people who fully  know or understand how these navigation tools work may be limited but didn’t stop them from successfully scaling and spreading. Geolocation has become so embedded in our lives that many of us feel lost without them.  Likewise businesses  like UPS, UBER or your local coffee shop depend on them to drive revenue, though only one may have incorporated the development and evolution in their long term planning.

Not everyone recognized how to turn the possibilities Geolocation enabled into successful business opportunities. The questions and issues associated with longer term technology changes were the focus of the January  Chicago Booth Strategic Management practices discussion.  The following summarizes some of the conversation exploring  the merits of planning with exceedingly long horizons, such as 10-20 years versus the common place three to five years.

A few caveats.

The discussion did not reference methods for engaging in really long term planning, and all acknowledged that predicting the future was not really the point. Instead we relied on a few articles (see bottom of the post), participants previewed in advance, to set up the conversation that focused on the necessity and benefits of formulating digital strategy.

We discussed the relevance of the horizon itself, and its power to dictate the frame of reference , “fix” the focus of  planning  that misses the ripple effects.  As one member explained, planning that focuses on the future, should also consider and think through how the choice and change in capabilities that your methods, processes and market dynamics preserve or inhibit your advantage.

In summary, we uncovered several strategic advantaged capabilities enjoyed by  only a handful of organizations who do indulge in a holistic long term digital strategy planning.  Take a look at what we discussed and tell us what you think.

Value of Subsystems

If we use the example of automated on the ground navigation systems , in hindsight, it’s easy to  imagine how many different industries and benefits would benefit from this capability. For example, the benefits to Triple AAA differ than those that would accrue to UPS. Imagine the steps in the plan that the former might have initiated.  Digitize the original triptik and triple AAA could distribute route maps cheaper, better and faster, right?  Nice plan, but much harder to execute.

The steps we can imagine might have been something like these.

1. Digitize maps by converting the physical visual information into searchable and thus manipulative format. Note, the task simplified by adopting pre-existing map making standards coordinates for longitude and latitude, as well as specifications for road type, elevation, distance, population density, geographic features, infrastructure etc.
2. Working in the address system, which varies in consistency within an area and across areas. For example, Chicago’s grid system makes it easy to pin down an address, than the numbering in New York city. Naturally, these numbers need to be linked to the map longitude and latitude coordinates.
3. Determine the accuracy of a given map and then keep them up to date. Roads are constantly undergoing improvement, and construction often adds or removes existing buildings changing addresses in the process.

Did you notice the subsystems that make this one idea easier to realize?  There are many more than I’ve mentioned, and consideration for each of them expresses why planning takes so long and can easily get very complicated.

Value of Experience and Re-use

Re-use, that was one of the first lessons I learned when I began to code (or write the instructions that allowed the computers to read/write different inputs to generate specific outputs. use, change data into output. To code from scratch was just plain silly. Chances were exceptionally high, that someone before me had code that worked and could accomplish at least part of what I was trying to accomplish.  It’s a simple lesson in systems too.  Systems, like problems, when broken down into smaller parts become easier to manage when you see and understand how they work.

The plan, or the idea may be inspiring but as Dwight Eisenhower remarked, it’s nothing, as planning is everything.

The value of planning often exceeds the plan because the experience of thinking through the subsystems can be re-used. The experience when shared also builds trust in the method and in your people.

Too often the focus is placed on generating a plan, and then backing out the projects that when successful will produce the results desired.  In a rapidly changing and dynamic environment, creating opportunities to challenge and improve our judgement coincide with opportunities to practice and strengthen competitive advantage by strengthening and promoting behaviors such as responsiveness, adaptiveness and risk taking.

Behavioral change, learning and knowledge acquisition take time and improve with practice. Notably it’s difficult to plan for disruptions, but we all accommodate and assimilate changes, the challenge is how to leverage this inevitability at an organizational level.

The obsession for clear return on resource investments compromises organizations’ long range planning or fully work through the possibilities of disruption and its effects. Similarly, few firms create the capacity and preserve time and talent permission for open experimentation and playing out multiple possibilities, such as Google’s Moonshot or Amazon’s generative experimentation. At the other end of the organizational spectrum, start-ups  do  take considerable risk to prove out their ideas only to change their focus and curtail their experimental capacity once they begin to scale.

So why do organizations continue to engage leadership in near horizon planning and even make use of social network technologies to broaden the input to include customers, employees and/or investors? Perhaps it’s a coping mechanism for the inevitability of change and a response to the dynamics of the marketplace while also garnering investor confidence, customer loyalty and employee engagement.  The tools that permit prioritization or even selection are more often based on the ability of the organizations to cope as well as adapt to the suggestions.

Leadership obviously plays a role. Perspective and ability to manage, versus address, the continuum of known possibilities limits their risks and accountability to short term while excusing their failings.

If timing is everything, then dealing with the here and now, and near, minimizes risks and costs necessary for survival but fails to secure competitive advantage.

This folly of short term thinking preserves alternatives over pursuit of a specific scenario of indeterminate future.

It was hard to explain whether the size of the organization determined its immunity from the dangers of failing to engage in planning with a longer horizon. No one had any experience that suggested larger organizations feel the pains of change sooner, or prove more or less resilient, adaptive to long term planning.

All agreed that understanding ecosystems, the dynamics of change warrant every organization to think through how these forces affect their organization not just in the near term but also long term.  More over leadership produces benefits when they increase adaptiveness and open mindedness.

Below are the articles we reviewed as the basis of our conversation.  Got anything to add, or suggestions for where we might find cases or evidence of the impact of long term planning would be most welcome.

Articles

Predicting the future, how to engage in really long-term strategic digital planning
http://sloanreview.mit.edu/article/predicting-the-future-how-to-engage-in-really-long-term-strategic

In the age of Autonomous cars, can your organization also be driverless
http://www.strategy-business.com/blog/In-the-Age-of-Autonomous-Cars-Can-Your-Organization-also-Be-Dr

AI, Self-driving cars and cyberwar, the technologies to watch for in 2017
https://www.theguardian.com/technology/2016/dec/25/ai-self-driving-cars-and-cyberwar-the-tech-trends

Transformation Readiness, is it the strategy of necessity or opportunity?

Change is something we live with, in large part because when it happens we tend not to notice.

In the 16th century, a philosopher of diverse interests astutely observed change as a relative concept which as an observer in motion makes it difficult to observe.  Change, when observed ultimately tests our understanding of time and I suggest adds meaning to much of our actions.

Change we make happen feels different than change that merely happens independent of our actions. What we make possible now becomes different than what’s expected and predictable.

Notable Change

Ever intentionally stare at something that over time gets closer or farther away?  You know the object travels distance, yet it’s difficult to perceive or notice its movement.  We perceive and understand change similarly, once we notice a difference we know change happened but unable to sense as it happens.

Traveling relative to moving fascinated Einstein too.  December marked the 100th anniversary of Einstein’s publication of his theory of general relativity. Naming, and then expressing the idea, requires different capabilities than understanding or theorizing the concept.

Ever try to make someone else understand something you know? Did you only use language? Or did you also use pictures, gestures? Analogy,  metaphor and  story all help others understand what you know, but until you actually do what you describe your understanding won’t be sufficient.

Scientists experiment in order to test out an idea they think works. In business, customers test the worthiness, or value of what the business offers. In both Science and business, it takes more than knowledge to be willing to test the idea. That extra ingredient I lump into a category I call readiness and its inextricably linked to change.

Perceivable change

Change, often defined as the difference between one point and another.

Point A                    Point B

•                                X

Take a look, how do you perceive change? General relativity explains that space and time both move, not exactly together, but relatively which like change makes the concept difficult to grasp, let alone measure.

Time keeping, now standardized, makes everything we do on earth measurable by contrasting it to the standard of time. Knowing the amount of waiting time helps us manage our attention by creating an expectation.  Standardizing time, allows us to plan and coordinate what we do for ourselves and with others.

For example, few people literally watch while waiting for a kettle of water to boil. The temperature of the water begins to change in the presence of heat. Reaching the boiling point proves to be a relative and meaningful change. Conversely, if the boiled water was used to brew tea or coffee,  knowing that without sustained heat, the same water will cool.

We experience waiting, not as the transitional changes in the water’s temperature, but the time difference between the thresholds. Placing a thermometer in the water allows us to observe  moment-to moment change in temperature but does little to change what we do while waiting. Similarly, the increasing number of installed sensors in the physical world  make it possible to observe the invisible moment-to-moment changes occurring around us.  Smart meters measure the amount of energy being consumed in a location, smart phones track distance traveled in greater detail than a car’s odometer.

Making change

What value does additional tracking offer?  Traveling, or consuming energy doesn’t happen because we measure them, nor does the rate in which change happens once measured.

Ever smile? This change we make in our outward expression isn’t always a conscious action and yet we may first discover by observing the reaction chain our smile produces in others.

If you want to understand change, try thinking about it with respect to time.  Actively trying to make a change happen helps us focus and notice the amount of time needed before the desired effect happens. Ever notice how long before others react to your smile, or until you feel water getting cold or getting warm?  Feeling the change in sensation doesn’t require quantification, or precision. Time too seems irrelevant, beyond our ability to recall.

When describing invention, as in the mother of necessity, what does this imply about our needs and our existing capabilities?

Possibility, are you asking how or what?

Polarity, the idea of opposites, turns thoughts and possibilities around like  a pendulum  always moving from one extreme to the other. That is until the thought runs out of energy or momentum and stops. It rests until some force displaces it.

Recently, a client asked for help explaining the difference between planning for a transition and planning a transformation. Since Transformation seems to be one of the buzz words of the moment, I began to wonder what made the two thinking processes different, and what did they really mean. My polarity thinking friend suggested that transitions plan for certainty, or near certainty and transformation plan for uncertainty.  I disagreed.

I think of a transition as the pause between takes, what happens between two clearly defined states.  It’s when we assess, evaluate or figure out our position, how close or far. Transformation, that’s the feeling we have on arrival, we made it so now what.

In other words, if the client has a clear objective as in to take a specific distant hill, then transition plans incorporate the certainty that elevations will be changing on route and insures the team’s prepared for the journey. When it knows  what changes to expect along the way, then it’s transition ready. Transformation focuses on arrival, different conditions and challenges it doesn’t know, but can imagine arrival makes possible.  After all, isn’t that why the objective was to take the hill?  Wasn’t it about the advantage that being on top offers?

Put another way, imagine what you want to do is known, like traveling to another location.  Transitions focus on the journey, how long will it take, buying tickets or planning the route. Transformation planning asks how the change in location affects your current activities.  Transitions are more whole body time shifts, where as transformation puts your head in the future while the rest of your physical body remains grounded in the present.

November’s topic for the monthly strategy discussion focused on Transformation Readiness. Before I managed to summarize the conversation and post notes,news about the sale of Mariano’s to Kroger caught my eye. and then I also spotted  an interview with CEO, Bob Mariano on the Chicago Booth website.

If you are not familiar with Chicago, then let me explain that Mariano’s was a new entry into the grocery store business. By coincident, just as they had opened a few stores one of Chicago’s main competitors –Safeway decided to close all of its Dominick’s stores. This meant Mariano’s acquired 10 of the closed stores and their debt fueled expansion took off.  That’s when Kroger came calling.

Since I had already been thinking about  transformation questions , as in how do you get transformation ready, I thought it worth sharing these responses.  Take a peek, and let me know what you think, are the example transitions or evidence of transformation readiness?

Scenario A: I think that Mariano’s namesake, CEO and founder, Bob nailed it when he said:

“At Mariano’s, we tried to push further. We continue to push.  What I mean by push is to expose the customer to different and unique things and allow them the opportunity to tell you, ‘No, I don’t like that,’ or ‘Yes, I like that.’”

Scenario B: Or maybe you prefer the spin by CEO of Shazam when asked about the increasing gap between growth in the amount of information and its utilization. ” …How do you improve data intelligence?”

“That’s definitely the case [that there is a data knowledge gap] and for years we have been talking about data warehousing, or capturing that data, but turning information into data intelligence is a new journey for many companies…”

Or, how about the Gambling industry insiders view who characterizes difference between digitizing or converting your industry to the reality post conversion this way:

Advancements in technology has brought about a rapid digitization of gambling and almost every other industry. Some have managed to exploit these developments more than others and I think that the gambling industry is at the forefront of how well technology can be applied to a domain.

As an industry we must be open to change and pro-actively look at how we can exploit such technologies to provide a better and more entertaining experience to our customers. For example, the progress in Touch ID has enabled us to allow LeoVegas iPhone app customers to log in to the casino using only their fingerprint.

Are you wondering why distinguishing between transitions and transformations matter? Or, even better, how your business can take greater advantage of the widespread availability, access and flexibility that a fully digitized world creates?

Great, now you are thinking strategically.

How Old Metrics may strand you strategically

Ever stop to consider how the ever present changes going on around you make your own transformation easier?

John Hagel relatively recent blog post describes the opposite.

In a world of accelerating change, one of our greatest imperatives is to “unlearn” – to challenge and ultimately abandon some of our most basic beliefs about how the world works and what is required for success.

Accenture a few years ago noticed that many different companies had shifted their approach to strategy. Perhaps, the availability of cheap, powerful computing capacity and Big Data are responsible for driving changes in strategy development as more organizations using technology find it easier to build consideration of the future into their present planning.   Hagel, a long time fan of scenario planning would applaud these efforts too.

With the rise of automated business processes, analytics too get incorporated automatically to enhance decision making and may be simultaneously compromising management capabilities to internalize all of these changes or understand the underlying dynamics traditional measures mask. Several articles provided case studies in different industries provided the basis of discussion around transformation (see the bottom of the post for specific article links).

Successful organizations rely on their strategy to put forward action plans, realize new ideas while averting risk. Statesmen and management alike find themselves in precarious places when they assume a trend will continue without change. Many statistical methods and decision-makers use of data remain unchanged from 1954 when Daniel Huff first published How to Lie with Statistics. His timeless book describes very simply the perils of improper use of methods that were designed to capture and explain if not contextualize the significance of singular observations, or data.   The current transformations enabled by technology have done more to alter behavior than organizations seem to recognize. That’s the path our discussion took.

The capability for insight

Prospective vs retrospective cohort analysis  and data mining techniques are far from new. Though the volume and speed of available data to digest and process with ever The increasingly sophisticated tools and the ease with which volume and speed of available can be processed may help as well as hinder their digestion. Sure the time to test alternative scenarios may be faster, but how do you choose the model?

Do you begin with the intended outcome? The scientific method and numerous models from multiple disciplines make it possible to isolate factors, determine their significance, and estimate alternative scenarios and assess how these variations produce changes in impact.

Similarly, the cross pollination of data modeling from one discipline into multiple industries and use cases continue to shift management beliefs regarding the importance of specific factors and interactions in their processes. The perennial blind spot denies many organizations and their leadership the insight necessary to transform both their internal strategic thinking process and business operating models. Last month’s discussion of McDonald’s and Coca-Cola illustrated how easily leadership misinterpreted fluctuating performance as temporal issues versus recognizing structural factors. It’s one thing to balance efficiency and effectiveness, quality and satisfaction and another to manage awareness of change and insights necessary to your continued survival.

What else thinking

“…both the digital world and the physical one are indispensable parts of life and of business. The real transformation taking place today isn’t the replacement of the one by the other, it’s the marriage of the two into combinations that create wholly new sources of value.  “

The sudden availability of online data tracking provided many organizations with the proper capability to understand user behavior differently. A whole new industry arose to focus on interpretation while creating of new measures while also introducing new thinking about effectiveness in sales, customer service, training etc.  Metrics, once created to prove out a strategy or an idea, now leave many organizations vulnerable until they build up the capacity to understand this new thinking let alone make corresponding operational changes necessary to sustain their business.

This is not the story of companies who fail to adapt such as Kodak who invented digital cameras only to retain their focus on film; but maybe it is.

Computerized reporting dashboards summarize specific indicators or activity associated with managing process or business relevant factors. The time and reporting cost savings that result from the automatic generation and ready access to information by managers and executives reinforce existing thinking and leave little room for understanding wider changes that may be impacting their business. It wasn’t long ago that analysts, and teams of them, spent their entire day pulling data and then calculating critical statistics detailing the effectiveness and efficiency of organizational activities to create reports for senior management. These efforts also made them accountable by insuring the data was clean, verifying whether outliers were real or indicative of a model failing to fully capture the wider dynamics. I was once one of those managers.  Today, automated reporting has eliminated many of the people capable of deeper data exploration and who chose what data, which statistics and the context necessary to understand the situation. The second problem is that data shared graphically or in tables never tell the whole story, though infographics do try.

A good analyst is taught to review the data and results, double-check whether the model or calculated results makes sense. Sure managers and executives may be quicker to detect aberrations and then raise questions but , how many of them have the time, patience or skills to test their ideas or intuitions? I imagine very few if any. Where are these available resources and how widely known are they to questioning executives?   How might the dashboard provide additional information to help frame the results executives see as they too seek to understand or make sense of the results?

Outside in thinking

Established data flow processes and automated reporting do deliver great advantages but they may also explain why outsiders find it easier than insiders to create new business models.   Where’s the out of the box thinking? And how can different data help?

Sure, it’s easy to blame regulatory requirements or compensation structures incentivized to focus on effectiveness and efficiency that leave little latitude to notice opportunity. For example, in the airline industry route fares were once set by regulations. The minimum fares were intended to cover airlines operating expenses that both insured passenger safety and access to air travel in more locations where market forces may lead airlines to cut corners. Deregulation may have given airlines additional freedom but many manage their business using the same metrics that they report to the Department of Transportation. Likewise in Healthcare, the imposition of new regulatory requirements came with new metrics that forced hospitals to focus on patient outcomes not just their costs.

When executives bottom line focus limits their thinking as an exercise in how making corrections in operation may maximize that number they overlook other contexts. Data quality issues should surface quickly in most organizations, but what if another factor created the data issue? A misplaced data point, or inconsistent treatment of the content of a data field rarely explain all aberrations in the results.   Weather, for example exemplifies a ubiquitous, exogenous variable. Observable data fluctuations may be directly or indirectly responsible by affecting other more directly connected factors, such as a snowstorms that change people’s activity plans. I’m not familiar with any automated reporting system that will automatically create a footnote to the data point associated with the arrival of a snowstorm. The reviewer is forced to remember or manually if possible add the footnote for others.

Bigger transformations to come

Bain believes there are significant implications for every organization that result from this digital and physical combination of innovations , they call Digical. It’s not easy to keep up with the corresponding behavioral shifts that result from these rapidly changing technological capabilities.

Focusing exclusively on efficiency and cost data helped management measure impact in the old era, though still necessary today they may no longer suffice. Do you know how social behaviors of your customers impact your bottom line? The technologies to support your business, such as your website or your cash register misses out on the social behaviors evident on sites like Facebook, Twitter, Yelp or even their bank. Mapping the ecosystem and then aligning the digital tracking data can now be supplemented with sensor data that may be anonymous to specific customers but can inform movement and actions relevant to your engagement.

Naturally, as mentioned earlier bias plays a role in our inability to notice the significance of new data. The more we automate and configure systems to measure what we always knew mattered, the less likely we are to be able to recognize new data and its significance. What should you the analyst and you the executive do to counteract these factors?

Takeaways

Monitor the activity of smaller companies as they experiment to learn what’s most relevant.

Don’t make assumptions, exercise strategic intentions to become more open receptive and curious about anomalies and be more creativity and persistent in identifying the drivers or possible factors.

Historically, metrics were an output designed to assess the validity of your strategy –did it work and/or deliver value. Not it’s time for strategic thinking to view metrics as an input. The use of statistics enabling analysis tools partnered with business knowledge and acumen must be part of communicating to higher levels in the business.

Often we measure the wrong things because the incentives are misaligned. Am I paid based on my proven ability to produce widgets at specific levels , or to produce effective, sustainable results for the business, not just my business unit?

Computers are useless they can only give you answers. For strategy, validating the questions may be important but so too is taking the time and effort needed to determine even better questions.

ARTICLES

Alternative case examples

Bain’s study and understanding of the state of “digical” transformation:
http://www.bain.com/publications/articles/leading-a-digical-transformation.aspx#sidebar
Fast Food
http://www.qsrmagazine.com/reports/drive-thru-performance-study-2014
Wireless
http://www.rcrwireless.com/20140812/opinion/reality-check-new-metrics-for-a-changing-industry-tag10
Television
http://fortune.com/2014/10/23/adobe-nielsen-tv-ratings-system/
Gaming
http://www.gamesindustry.biz/articles/2014-03-10-social-currency-has-real-value

What strategy will help Coca Cola and McDonald’s continue to Grow?

McDonald’s and Coca-Cola, two of America’s most iconic brands were the focus of the January 2015 discussion.  Why pick on them?

1. The market has been digesting repeated disappointments over quarterly earnings and fueling speculations about their future.
2. The availability of ample data and a broad set of analyses serve up a perfect opportunity to further our own understanding of the strategic challenges related to sustaining growth.

Typically, most organizations begin a strategic assessment with a simple SWOT analysis.  Instead,  we followed the Chicago Booth tradition and began with a look at available data.  We reviewed a  series of articles before discussing these two companies’ prospects for future growth. (Click here for the links and discussion preview.)

Both companies offer evidence demonstrating how their history and initial value proposition continues to dictate their forward strategic paths. Or as Michael Porter would say,

“Strategy 101 is about choices, you can’t be all things to all people.”

Once you decide whether your organization will be a cost or benefit leader, aligning your resources and messaging becomes simpler. Price doesn’t fully substitute for quality, and consumer preferences are not always consistent. An organization’s successful growth demonstrates it’s priorities and reflects its consistency to deliver on its commitments to customers and their preferences centered around price or quality.

McDonald’s and Coca-Cola sensibilities and capabilities embody the management principles of post war industrialization. The hallmarks of efficiency embodied by these two brands commanding distribution networks reflect their unwavering commitment to quality, consistency and convenience. Each however has defined value differently in the eyes of their customer which further enabled their brand’s rapid, organic growth.

McDonald’s initial automation and efficiency enabled it to deliver meals affordably, conveniently,consistently in an atmosphere that maintained a high standard of cleanliness equal or better than its competition. In 1953, these standards proved themselves effective differentiators.

Coca-Cola chose to deliver on the benefit side, historically limiting its physical assets and focusing on relationships, advertising and consistency around quality.

Operating within the boundaries of these original value proposition, both brands performance over time demonstrates how their responsiveness and sensitivity to regional differences and changing customer sensibilities allowed them to continuously add value and grow. Each brand’s commitment to experimentation and innovation proved central to fueling organic growth. Further,  their individual strengths allowed them to leverage new ideas, even when introduced by competitors.

In 1963, Coke’s introduction of TaB followed the success of Diet Rite Cola, a first entrant in the sugarless soda category. In 1962, McDonald’s introduced the Filet-o-Fish as a meatless alternative for observant Catholics following the suggestion of an Ohio Franchisee responding to local competition

For each, their share of successes also included colossal failures. Who can forget New Coke, or McDonald’s Arch Deluxe? Per Daily Finance.com these two were the #1 and #4 biggest product flops of all time. Both however learned from these experiences and were quick to renew the good faith of their customers and keep growing.

That is until now.

The value defined by their strengths, brand status advantages and considerable market dominance delivered significant success, but now cloud their vision and impede their path to future growth. After all, what’s really left for them to tweak? What haven’t they tried and learned?

Beyond Strength

Both companies continue to demonstrate long term value for their shareholders.  Each provide great capital returns and margins.

• Coca-Cola has paid a rising dividend since 1963 and has a current yield of 2.88%.
• McDonald’s has paid a dividend since 1976 and has a current yield of 3.72%.

Each holds the leadership position in their category, continue to show signs of forward thinking and planning at levels of coordination and integration that few companies achieve. Their initiatives, irrespective of success rates are also lessons and templates offering competitors a looking glass into the future.

According to data from the National Restaurant Association, fast food accounted for about 28% of the $683.4 billion in overall U.S. restaurant sales in 2014. The Palo Alto Medical Foundation reports that 25% of Americans eat at fast food restaurants every day.  . Quick Service Restaurant (QSR) magazine identified McDonald’s as the world’s biggest restaurant chain by revenue-$36B in US sales in 2014.  This equates to an estimated 18.6 percent market share of the entire fast-food industry. (Per IBISWorld market research 2014 as reported by franchise chatter.)

“McDonald’s stands for value, consistency and convenience,” says Darren Tristano at Technomic,”and it needs to stay true to this. Most diners want a Big Mac or a Quarter Pounder at a good price, served quickly. And, as company executives now acknowledge, its strategy of reeling in diners with a “Dollar Menu” then trying to tempt them with pricier dishes is not working.”

Just as McDonald’s typifies the fast food industry, Coke is the soda industry, or as Mike Weinstein, a former president of A&W Brands told Business Week,

  “Whatever Coke does, it’s seen as what the soda industry does. What happens to Coke eventually happens to everyone.”

And So?

The strengths of these two brands and value propositions sound good for McDonald’s and Coca-Cola. Their future growth however depends on just how they renew their efforts and focus and capitalize on their key strengths. The forward position challenges you to see and respond to changes  in your business environment faster. Their sheer size and market share visibility also make both more vulnerable to wider market pressures.  Especially in the U.S., where both companies current experiences and declining sales volume indicate they somehow misread the significance of changing American attitudes  around nutrition and choice.  For example,  the 3% decline  in 2013 of the entire carbonated drink market in the U.S. hurt both companies’ sales.

For Coca-Cola, the emergent energy drink category displacing their sales creates challenges for which they  have not had an effective response.Similarly, the alternative fast growing Fast Casual category represents McDonald’s biggest threat. Further growth in this category limits further expansion in the corresponding Fast Food category, and McDonald’s too has yet to effectively compete.

In addition, both new categories prove highly appealing to millennials whose behavior and preferences some analysts contend prove influential to other segments. No wonder both brands chose to leverage their considerable resources around what they know. Each reportedly are investing $1bilion in advertising in efforts to re-establish awareness among this key market segment.

Holding the value of your brand

Interbrand’s 2014 Best Global Brands
2014 RANK	2013 RANK	BRAND	SECTOR	2014 BRAND VALUE (USD $billion)	% CHANGE IN BRAND VALUE
1	1	Apple	Technology	118.863	21%
2	2	Google	Technology	107.439	15%
3	3	Coca-Cola	Beverages	81.563	3%
….		….
24	22	Pepsi	Beverages	19.119	7%
38	37	Nescafe	Beverages	11.406	7%
72	69	Sprite	Beverages	5.646	-3%
….		….
9	7	McDonald’s	Restaurants	42.254	1%
68	66	KFC	Restaurants	6.059	-2%
76	91	Starbucks	Restaurants	5.382	22%

Source: Business Wire, Oct, 9, 2014

As shown above, in 2014 Coca-Cola’s increased its estimated brand value of $81.56 billion 3% from 2013 permitting it to hold it’s #3 position a second year in a row. This is after losing the #1 spot it held in 2012 and a decade long decline of American soda sales. Their continued brand dominance reflects the impact of their recent marketing, acquisition and diversification strategies.  Business Week explains it this way:

“In 2007, Coke found that 20 percent of the sales and 50 percent of the growth in the $120 billion beverage industry came from small, independently owned brands, a third of which hadn’t existed five years before. That year, Coke launched its Venturing & Emerging Brands (VEB) division to cultivate relationships with and ultimately purchase some smaller startups.”

In Contrast, McDonalds estimated brand value of  $42.2 billion increased only 1% over 2013 reflected its slowing growth and dropped it to #9,  down from #7 position it held in both 2013 and 2012. (Note the distance between these icons and their nearest category competitors shown for comparison).

The marketplace loves a good story of failed leadership. When the mighty fall the press and public are quick to pounce and in some ways, fresh eyes and alternative experiences and optimism may prove more than beneficial. Will activist investors get their way?

Then again, in taking a close look at the fundamentals of size and respective asset valuations our disccusants were reminded of the difficulties around sustaining organic growth.

Below you’ll find the participants takeaways following our most recent discussion. Read the articles, see if you agree. After our usual wrap-up, you will also find a series of simple questions we plan to raise with a few folks with deeper knowledge and a more intimate understanding of McDonald’s.  We will post their responses when they arrive.

TAKEAWAYS

• The one size fits all notions that produced cookie cutter efficiency and passed on volume savings to maintain quality suited the growing quick service restaurant category, when there were few comparable alternatives. Today, the US market especially its urban centers, reflects far greater diversity in the category. The growing variation along the price value continuum illustrates the market’s response to changing attitudes, palates and preferences of consumers as well as differentiating  perceptions. Use your strengths to build alternative restaurants, maybe tailoring them  to regional preferences and further diversify your portfolio holdings.
• Separate the brand from the occasional value meal inspiration.  Sure everyone appreciates getting the best value for the lowest price, but it’s difficult if not impossible to deliver differential value messages within the same location as in the value meal combination vs. purchasing off the dollar menu. Turn your attention to differentiate your value relative to your competitors at similar price points.
• The strengths that prove appealing to shareholders don’t indicate your understanding of individual customers.  Declining customer counts along with infrequency of return visits suggests the absence of resonating experiences necessary to meet the demands of the increasing segmentation within your broader competitive category. How can you continue to benefit from your existing strengths? Pare down your menu further to deliver the essentials of what your core customers want, assuming you really understand who that is.  Once you do, use a loyalty program to reward them and keep closer tabs on their responses as you continue to test.
• If increasing customer price points is key to your growth equation then you also need to offer higher value for the price in order to avoid losing the core brand identity.  Obviously in rural areas where the choices are fewer, you retain a firm grip on the market and can delay changes. Unless the $1 menu, or $1 menu plus offers acceptable margins you may need to find alternatives to pass your volume discounts on to consumers.
• Separate supply and demand functions as you manage the business going forward.  The benefits from your superb asset management capabilities on real estate, currency risk and supply chain have been impeccable and thus puzzling to watch your miss on the demand side. Are there lessons in creativity and management that could prove helpful?
• The proliferation of segmentation in the marketplace let alone in your customer base requires a more innovative approach than mere brand building activities offer. In focusing on the customer experience you may miss aligning around your core identity. Another reason it may pay to try an alternative diversification strategy through new restaurants, concepts that don’t compromise but complement the existing franchise.
• One of the problems of being so big and maintaining a healthy distance from your nearest competitor means you were insulated from the small ripples of changing sentiment that others were quicker to seize upon.  Your crumbs became their meal and growth ticket.  In order to get out front again, you may need to get much closer to your customers, and surprise them, delight them or even choose to get cozier with your competitors again to find a way to grow the category together.

Concluding remarks:  We know we didn’t discuss Big Data or social media or even mobile so there’s plenty of things we missed in 90 minutes. Please, share your suggestions or comments on what you find to be effective growth strategies for market leaders who seem to have hit the end of their runway.  We’d love to hear from you.