Mobile Strategy–an imperative for your future

Note to readers: The graphic to the left was found After the  October 18, 2013 discussion, inspired by articles listed at the bottom of this post.   

Does your near term performance hinge on your understanding of mobile  technology, and if so, how critical a role does it play?

Infographic-2013-Mobile-Growth-Statistics-MediumToday mobile platform adoption rates outpace the technology’s downward pricing.  The dual benefits of convenience and constant connectivity offer irresistible value and overwhelm the initial cost bumps associated with implementation.  It’s not merely the anytime anywhere connectivity with your social network that makes mobile valuable. Mobile technologies offers direct access to increasing varieties of information at the tip of your finger anytime and every where (if there’s wifi).

Questions that used to leave us uncertain, can be easily answered.  For example:  How soon until the next bus arrives?  What’s the best route to any intended destination?  What can I make for dinner? Who has the best price? What’s the name of this song playing right now?

Short message services–SMS, Geo Positioning software – GPS, Google search, untold numbers of product and service applications and internet browser capability are now built into multiple mobile devices.  They allow everyone to travel lighter and access the information needed at the right time.

For business, if you don’t have a mobile strategy yet,  best make it a priority.  At least that’s what the discussion participants concluded.  Skeptical of consumers ability to fully integrate many of these technology opportunities into their daily routine or modify their existing habits and behavior,  companies who have yet to play in this space will find it harder and harder to catch up.

The strategic opportunities continue to evolve in tandem with the spreading  uses for assistive mobile technologies.  For example, a prudent strategy  in consumer marketing might be to incorporate  the technologies to enhance the user experience—especially as no clear killer sales application that deploys these technologies exist.

·         Amazon with all its technology savvy and leadership in the online sales market leveraging its platform hasn’t found a way to fully leverage mobile capabilities to increase sales.  Mobile assistive technologies, like Google maps represent a hybrid.

·         Twitter, hot off its successful IPO has yet to grow actual sales for any business.

·         Facebook’s use of GPS allows business to learn more identifiable information about the consumers as they become proximate to their store,  but have yet to prove predictable in driving retail sales.

Advantage

What advantage then can mobile technologies really deliver?

There seems no limit to the additional utility Search Engines provide.  Mobile technologies allow roving users access to  public, private or personal sources that the engines verify and validate boost both their value and help build loyalty incentive programs.  Increasing numbers of gamification applications also exemplify how mobile technologies drive growth opportunities  by enabling repeat sales through mutual identification of merchants and existing customers.

More interesting,  mobile technologies helping to optimize each stage in the sales cycle sequence.  Applications that make use of two way transmission—driving traffic both by or to customers is just the beginning.  Efforts that allow discovery and exploit more stages in the cycle help determine when, where and how the transmission proves itself  more efficient and effective.  Should your business deploy mobile to simplify checkout? Or simplify merchandise location and availability?

In the ongoing evolution of technology, strategy that focuses on deploying tools for competitive advantage or advancement isn’t enough.  Strategy needs to consider how the new technology influences your revenue flow.

Possessing mobile technology isn’t merely a lower cost play. Strategic opportunities increase when it’s used intentionally to offer stakeholders learning opportunities.  Can you give your sales people the most up to date information on the customer’s past purchases, or your customers’ suggestions for product use, installation or enrichment?   Present technology capabilities and big data offer business opportunity to accumulate metadata and create richer customer profiles.  Mobile brings them together by putting the specific customer into the present transaction equation.

15 years ago, business wondered how, what and when E-Commerce would change their reality.  Today, forward planning organizations recognize mobile technologies as a similar force of permanent change.  Advantage will flow to those organizations who get out to test and experience for themselves the many features mobile technologies offer them directly.  These options offer unique understandings and help them translate mobile technologies’ anytime, anywhere access options into business value.

Strategy that activates customer and supplier value goes beyond capturing attention and offering incentives to drive traffic.  The strategy must consider the fuller customer experience and increase the odds of success by investing in developing future capabilities such as cross training staff and directing resources that  effect cross-promotion , understanding  both crowdsourcing and influence peddling opportunities.

Walmart’s recent experience demonstrates the shifting control customers now possess.  A computer glitch with  the Federal WIC program’s system communications prevented enforcement of  purchase limits at Walmart’s Point of Sale.  A customer tweet  flooded Walmart with these customers who exploited the system failure to their advantage and  Walmart received the short term benefits.

Summary of take aways

  1.  Confirmation that organizations must be actively trying to understand the technology, otherwise they may never get the benefits.  For now, obvious value is limited to facilitating adaptions to  marketing .  Eventually both seller and buyer will reach the same understanding but the advantage will continue to flow to those who worked hard out front and made it easier for their customers to both benefit and settle in as they who to trust and where to be.  Switching costs are always serious and so it pays to be out front.
  2.  Best to think through how you deploy these technologies carefully.  What opportunities will make things easier for you consumers, and then work to simplify the individual steps and actual transactions.  For example, Millenials view mobile as an essential service and continue to need and expect universal Wifi and battery charging wherever they go.  Are you helping them?  If not, your access to this key demographic will be limited.
  3. Balance the cost/benefit of information and investment.  Mobile is a work in progress like any technology, don’t put all your eggs in one basket.
  4. Opening up of information transmission in more places and with more transactions suggests that additional paths to capitalize on this phenomenon.  Your strategy should seek to know and learn, as in where you can produce added convenience, respond and simplify steps in your own or your customers’ process, find out more about customer behavior and your ability to learn with  them  in order to  gain strategic advantage.
  5.  Continue to seek out pockets of advantage—customer  loyalty is easy, instant access, centralize connections for your customer to one place is another.
  6. Transparency too is key. Mobile comes with real time imperatives and be sure your back up plans work.  Open Table app for example failed to deliver real time answers or reservations, which diminished its value and its opportunity to build customer loyalty.

ARTICLES:

Mobile Now—Strategy +Business June 2013

http://www.strategy-business.com/media/file/00196_Mobile_Now.pdf

The 6 Biggest Mistakes Made on Enterprise Mobile Strategy

Posted by Adam Bookman in Wired on August 5, 2013 at 10:30am

 http://insights.wired.com/profiles/blogs/6-biggest-mistakes-mobile-strategy#ixzz2glZMCXXu

 Global mobile statistics 2013 Home

http://mobithinking.com/mobile-marketing-tools/latest-mobile-stats

And, an Optional  case Illustration.

A look At Quiri- Retail Intelligence using mobile crowd workers

http://techcrunch.com/2013/10/02/quri-a-retail-intelligence-platform-using-mobile-crowdworkers-scores-10-million-from-matrix-others/

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BIG DATA: Big Deal or Just Big Business?

Technology evolves and for those of us who spend their lives adapting and endeavoring to keep up with the advancements it’s hard  not to notice a curious underlying dynamic.   Data and our ability to calculate or manipulate it for greater meaning is a little like resolving the chicken and egg paradox.  More of one begs more of the other, and yet we continue to ask which came first as if that question were important.  For many of us, our interest in  closing the uncertainty gap wishes for more data. We expect it will  help minimize the error or noise because the present picture of relationships remains a little too ambiguous. The constraint in this case is often our own experience and knowledge.

Professionally,  my own work warns against this unconscious bias.  I simply ask people to imagine three dots and ask that they line them up.  I then remind them that all three dots are coincident data points in time, and ask whether this new piece of information has changed their vision of the dots?  I then ask them to place the dots on an axis of time, and tell them that the dots now represent demand, growth or performance like ROI.  Does the way you’ve visualized the dots changed again?  I explain that the context I’ve added snapped into their own experience to create an image that creates a new puzzle as what they see fights with their expectation and they need more data to explain it.

The Economist in revisiting the Growth Matrix in 2009, put it another way. Bruce Henderson, credited with originating this framework reportedly believed  “while most people understand first-order effects, few deal well with second-and third-order effects. Unfortunately, virtually everything interesting in business lies in fourth-order effects and beyond”.

Big Data and the volume variety and velocity of its availability now has several partners,  real time processing power and plummeting data storage costs and lest we forget, simple access and manipulation tools  placing the data in an ever increasing number of users’ hands.  It is the number of people who now want to use the power of analytics that lends Big Data its influence, or at least that’s what several Chicago Booth alums who shared their thoughts last week recognized.

On May 18, 2012 Chicago was busy preparing for the arrival of NATO delegates and support.  The result was many businesses strongly encouraged their employees to work from home, leaving the monthly strategy discussion homeless.  We took advantage of the opportunity to launch our first virtual discussion combining a real-time interaction platform  (Group Systems Thinktank) and conference call (freeconferencecall.com).  Interest in the topic proved overwhelming prompting us to open up a second lunch interaction following  our usual early morning time.  The comments that follow represent a condensed version of the conversation.  Note, links to the discussion prep video and articles we encouraged participants to review in advance can be found at the bottom of this post. Also, a full transcripts are available to those who interested in seeing the automated output from ThinkTank, just drop me a note.

What’s the deal

Its a toss up whether mobility or big data has captured the imagination of business media more. The duel isn’t the point. Other driving forces and a growing need for critical thinking skills that were already in short supply.  Data reduction may be an emerging competency.  As the earlier references to Henderson point out, the questions you are trying to answer don’t get any easier just because you suddenly have access to more data. What to do with this new wealth of rich information are the bigger questions and challenges not merely for business but for consumers as well.

In the process of  generating the following list of examples, the interaction on Thinktank let participants also provide some links, raise new questions and add additional comments.

Twitter ,Telephone call records, Smart Grid, Real time Electricity meter  data , Nike + ,Scanner data,  Comments from Call Centers,  Providers’ case and disease management notes, EMR records, Geospatial (GoogleEarth, Navistar, etc), Mobile and GPS,  Gov’t DBs (big-data in an unstructured/non-uniform sense) , The quantified self, Output or processed Data from SAS, Salesforce.com, other enterprise databases, Loyalty program, Amazon purchase history, Mint.com, Moneyball (Big data in baseball), the new NSA data warehouse in Utah, QR, The internet of things, Data.gov, The London Datastore, created by the Greater London Authority (GLA–Chicago has similar initiative) offers citizens open access , Netflix movie recommendations, SAP’s HANA usage (profiled in the report on their Sapphire Conference )

Twitter for example has evolved in ways that surprised their founders and also launched a number of new businesses with very unusual purposes. As one article pointed out routing the data can be equally important as tallying it, as illustrated by Procter and Gamble’s practice of funneling social media conversation/data to the appropriate person’s screen for monitoring and response.  In other words to be meaningful, sometimes just knowing something happened is enough, it doesn’t necessarily have to be mathematically manipulated to derive value.

Persistent challenges remain in dealing with the enormous variety of formats in which data are presented — some  sources are difficult to analyze — their pages long data dictionaries  often include details about its collection.Add to that the realization that Data is not just numbers anymore. The automatic semantic annotation required to make sense of this has also entered a new era.

Facebook, LinkedIn, Google+, Pinterest and similar social media sites would fit in here, as well.  All offer a richness of information, much of it real-time, that can be monitored, mined and used to drive decisions and actions. The customer center conversations , or customer audio recordings , transcribed to text, and then subjected to text analytics is helping improve performance management practice, allows for campaign conversion performance tracking etc

The impact or convergence of the evolving technologies with all of this new data, is as overwhelming as the scanner data that was available and stored historically but few had resource capability or interest in mining it. That era has passed and with it, new questions and promises arise.https://i1.wp.com/www.connectedaction.net/wp-content/uploads/2012/04/20120421-NodeXL-Twitter-Global-Warming-Labeled-Groups-Network.png

Can we better understand and use consumers sentiment as in  do retail customers use more electricity/phone service/etc in a method that correlates to changes in the economy? weather? Or SAPs HANA data, now makes cancer DNA genome type analysis possible in minutes.

FB and Twitter,  may be drawing more attention, but those who  bring together the different streams  and mining more deeply old sources such as scanner data  are also causing quite a stir. Target found out that teenage girl was pregnant before her dad did using methods such as these.

Add the RFID  and imagine the benefit to stores knowing the quantity of each SKU that they currently have?  Can they coordinate sharing of product between their brick-and-mortar stores?

Perhaps the focus on twitter, etc., rather than scanner data comes from hoping that trending sentiment will precede and can be used to predict purchase, rather than log it as with scanner data. At cars.com, a participant shared  that vehicle search data on our website is predictive of sales.

It looks like QR codes might achieve the same benefits of RFID as smart phones are becoming ubiquitous.

The Geo-spatial data, according to McKinsey’s recent report on Big Data as the next big innovation, quantified billions in time savings from just helping consumers avert traffic.

Several other behavioral nudging based on real time feedback is now possible. Nike is exploring and furthering this automatic feedback. Check this article for more brands using the quantified self, and more information

TOOLS

SAP’s HANA, Google’s BigQuery , Splunk, Hadoop and NoSQL databases , Tableau, Tibco Spotfire, Omniture ,Pentaho (open source BI), Amazon’s Web Service suite (more of a platform), Cloud computing platforms, Data visualization, most business users, make the data preparation easier and allows them to focus more on analysis and develop insights in combination with Machine learning tools (neural networks, support vector machines, natural language processing, etc.)

Decision making , can and does BIG data make more accuracy possible?

It offers higher granularity — like Target’s ability to create coupon books customized to individual households, Or integrate GPS level stuff — e.g. texting coupons to customers right while they’re standing next to a certain store.  Or 2nd/3rd order analysis – correlating Target’s sales with weather data; creating ‘real-time’ personalized coupons; identifying ‘trend-setters’ among the customer base to influence ‘trend-followers’ coupons

The downside? Detecting or separating out spammers from these data sets or paid to  express a certain sentiment. Totally! Like those girls paid to say great things about clothes on Facebook — not maybe necessarily analyzing big data, but using the platform.

Greater real-time evidence  can reduce risk and  insure assumptions in product/service development and marketing are on or off target.

Hard to appreciate the analytic without the qualitative context or understanding;  but maybe some strange new ideas can come out of the data, like the “diapers next to beer” epiphany. Data needs some drivers to make it meaningful, as in cause and effect. In part because qualitative data is harder to analyze.

Is quant vs. qual or the social science methods to data collection really that different from the scientific data analysis approach?  Both approaches seek to explain cause and effect, or the relationship between a stimulus to produce a predicted response. The problem is  too many people will extend a model beyond it’s capacity. Claiming “the data said so”  lets people off the hook and avoids responsibility for  decision-making.

Suggested tips include  avoid extending a model beyond its capacity, or  understand and differentiate descriptive and predictive Stats. Likewise, be wary of  finding trends that don’t exist (e.g. “data mining” or “straws that look like needles”) and confusing correlation with causality.

Perhaps cross-validation from trained analysts can help avoid  these . Danger of expecting tools to automatically extract value from large datasets.  Need to ensure good analysis, disciplined hypothesis generation, etc.

The data, even when analyzed, does not represent the decision.  This is true with small and big data.

FINAL TAKEAWAYS

 

  • Big data is here to stay – need to figure out how to use it effectively.
  • I liked the point that lots of data is around and that people just don’t know what to do with it.  The best BIG DATA process or engine in the world still won’t create the insights that are needed.
  • Corporate culture is a huge factor–the problem is not availability of data, but commitment and focus of corporate leaders to shape a culture that moves the organization in that direction.
  • Big data is here. It’s a tool and like any other, it’s the latest and greatest on the block, with a bit too much hype. But it has a definite value in providing and stronger qualitative base to identifying trends and activities.
  • My realization  is that, once again, the technology is interesting, but it is the corporate culture and will that will matter. The culture and vision lead; the strategy and models follow.
  • sharing the questions with a wider audience confirms concerns and clearly lots of assumptions that need to be played out. There is a large dark side that we still don’t understand; but the positives and opportunities for real time decision.
  • Big Data! The piles get higher and  higher and wider and wider…to what purpose? That implies the need to “mine” the data, reduce it and subject it to analysis before it can be made useful.
  • Big data will revolutionize business but it is not strategy, potential for a lot of false positives .
  • The wise use of big data offers a huge opportunity for developing differentiating strategies and for finding new product/service needs.
  • “Big data” is the current term for things that have existed for a long time.  All types and sizes of organizations can benefit from big data if they recognize the importance of the human component (not just the data and software) and have specific objectives in mind before starting.
  • Much of the expertise about analytics developed over many decades still applies, and there are new dimensions to integrate and understand because of the availability of the technologies and data.
  • Everyone on the line has experience with Big data, so I don’t think it’s so scary.  Most people have business perspectives, wanting to teach the Analysts that their conclusions need to be driven by business needs.   My comment is that as leaders, and those trained with some behavioral awareness through business school, it is _OUR_ responsibility to try and massage the analysts towards an enthusiasm for our world view…;-)
  • The human side of utilizing the technology and expertise is just as challenging as ever. (Cognitive biases, communication skills, influencing skills) Garbage in – garbage out is a big risk without proper attention and skill in applying the technology and in communicating.  The data, even when analyzed, does not represent the decision.  This is true with small and big data.

In closing, let me return to my observations about the limitations of developing strategy rooted in an expectations of the experience curve relationship.  The frame with which you approach the problem often has far more bearing than the data, your analysis or the tools.  Or at least, in June we  plan to look at some of the assumptions around growth as the ultimate strategy.

Please throw your responses, or continue to post links for others as Big Data continues to be quite newsworthy as its impact and influence continues to unfold.

Articles and links:

We suggest an  Optional  short 5 min. video tutorial , EMC produced to understand what Big Data IS?    http://youtu.be/eEpxN0htRK
The following are required advance reading.

1. IBM’s Institute for Business Value, in collaboration with MIT Sloan Management Review  2010 research findings
Analytics: The new path to value: How the smartest organizations are embedding analytics to transform insights into action

  http://public.dhe.ibm.com/common/ssi/ecm/en/gbe03371usen/GBE03371USEN.PDF

2. Strata keynote  short 7 min. video by Google’s Digital Marketing Evangelist Avinash Kaushik- a bit irreverent and a little over the top – a bit irreverent, bordering on over the top – but not boring  effort to help us understand the problems and the approach undertaken by Google.

Big Data Imperative 
March 2012
http://www.youtube.com/watch?v=CrSX97elHDA

3. Tom Davenport’s Culture of Analytics

April 5, 2011
http://smartdatacollective.com/clifffigallo/34719/tom-davenport-s-culture-analytics 

4. Inside P&G’s digital revolution
McKinsey Quarterly November 2011
http://www.mckinseyquarterly.com/Retail_Consumer_Goods/Strategy_Analysis/Inside_PGs_digital_revolution_2893
overseeing the large-scale application of digital technology and advanced analytics across every aspect of P&G’s operations and activities—from the way the consumer goods giant creates molecules in its R&D labs to how it maintains relationships with retailers, manufactures products, builds brands, and interacts with customers. The prize: better innovation, higher productivity, lower costs, and the promise of faster growth…

One more optional overview

The age of big data
NYTimes, Feb 2, 2012
http://www.nytimes.com/2012/02/12/sunday-review/big-datas-impact-in-the-world.html