Time is money, are you using real time data wisely?


busby-berkley-snowflakeTime is money, are you using real time data wisely?

Are you feeling up to date, in sync with the times? Both individuals and organizations find it challenging to fully leverage technology and integrate the sea of real time data that surrounds us.

This past week, I attended a local Internet of Things (IOT) conference, only to be reminded how we’ve been kidding ourselves with respect to the human machine dynamic.  When Factiva reported in 2013, that the previous two years had created 90% of the world’s data, it also reflected the impact of visibly faster technology and emergent opportunities for those capable of wrangling more data. Similarly, the exchange of information machine to machine and the responses that  IOT and the Industrial IOT (IIOT)  make possible  will soon surpass all human generated information.

Information has never proven more valuable to competitive advantage than now. The key istimely mastery and/or the ability to separate meaningful data from noise. Possessing  Real time capabilities merely up the ante. 

Suddenly,  all of the conversations about the real, meaningful  difference of  Big Data clicked. The challenges I knew and had experienced working with volumes of data is not something everyone experiences, and itswhy I missed the significance of the message. Language can do thar. Today’s – competitive advantage relies on learning synchronicity between people, and also between people and machine. 

Yep, syncing as in coincident timing. Timing reactions require coordination on the order of the elaborate dance numbers Busby Berkley made famous will separate winners and losers. 

People learning rates

People are interesting precisely because we begave inconsistently.  These same traits  make us effective competitors and efficient information processors.  We focus and only selectively pay attention, which means we consciously ignore most information in our midst. Unlike machines, we are slow few of us possess capabilities to process high volumes of complex data at high speeds. 

How people integrate data remains a bit mysterious. Part conscious and part unconscious, each of our senses connect to different parts of our brain and the information isn’t always processes with consistency. 

Humans create their own reality. For example, our eyes see things differently than what we describe and not because of language problems. Automatic transformations correct using depth perception and pre existing knowledge to flip the image, while sound tends to retain its integrity. 

Similarly, information new to us versus updates also  process differently; and yet, endless streaming information can overload and confuse us. Today’s powerful computers don’t experience anxiety or fatigue though they may overheat or fail.

The natural limits of time and energy challenge people to choose their focal point, the when and how we respond to data and perceive opportunities. For example, few of our waking moments and activities require conscious thought. Our body takes care of itself and manages to coordinate processing of external sensory information with internal demands. This syncing makes possible mindless activities like breathing, eating, walking and resting.

Consciously, our ability to track our time and energy is spotty.  Still, unstructured/unplanned  moments, especially those that demand little of us mentally remain ideal, while society frowns on the same characteristics when referred to as idleness. The contradiction reflects the value we attach to purpose or meaningful use of effort over time that results in tangible output.

Artists create, builders build, analysts compute and chefs cook for example by adding their effort over time. They make something or transform original materials/inputs.

The notion of efficiency also boosts the value of effort by measuring the effort relative to the output produced over time. Likewise effectiveness, measures the additional value produced relative to the starting inputs. Together, these measures translate into meaningful consistent tokens of value that permit ready exchange, or wealth accumulation.

In this context, the accumulated tokens of value allow us to buy ourselves time to take vacation or be idle as easily as buy us time to learn, create and do more.

Machine learning capabilities

This also explains precisely why technology advances prove so valuable, as they have progressively reduced the amount of time and effort necessary to perform a task. As a result, we DO spend less time on common, routine activities than was previously necessary.  Internal plumbing saves us time we spent fetching water, Wheeled transportation saves us time we spent walking, and similar telecommunications vastly removes the break in communications that once necessitated considerable effort  to cross the distance by one if not both parties, or the enlistment of a proxy to carry the message on their behalf. The human messengers were replaced first and written notes/letters, and then the telegraph dramatically reduced the time between message sending and receipt.  Now text messaging and email is displacing telephone and video conferences.

This evolution in communication methods affects the people’s interaction styles but also their information needs and expectations.

Real time communications savings and benefits are not equally distributed and so inefficiencies persist.  On one hand they present a new opportunity to replace planning and documentation of activities essential when communications were primarily indirect and time lagged. Built-in tracking, boosted transmission capabilities and data recording can both fill in and increase information gaps.  Problems associated with incomplete, unsupported or even delayed information that always created risk persists, but for new reasons.  The flood of data from more sources both people and machine generated pose new challenges to separate out meaning, predict and or respond in timely, relevant manner.

Another opportunity real time capabilities offer are all around us, assisted by the information collected and transmitted from multiple data sensors scattered across the environment.  In fact, it’s how airplanes fly automatically, rail road cars notify switches of their location to either open or close crossing gates, motion sensors in buildings adjust level of lighting and air temperatures, and Tsunami warning systems saves lives.

In general, people are wired to process information in real time. We use an array of body language cues to understand how to  manage the situation and engage with the people in our midst, and yet we do it unconsciously.  Planning on paper is a far more conscious activity, time consuming and energy draining.  Worse, planning often stops us from activating the unconscious real time processing.  We follow the plan, rather than notice the inconsistency or the more obvious information we may or may not have incorporated.  Best example, is the step by step navigation systems that we know are less than perfect.  Have you found yourself using the navigation only to discover it’s asking you to turn onto a one way street going the wrong way? Or your location is “ahead” of the GPS signal and so you miss a turn?

My point is this.  Too many built in business procedures and processes were designed in the absence of real time information.  In order to be more relevant, more valuable people will need to revisit their processes with respect to learning, creating and doing.  It will require a shift in attitude, refocus of needs and adjustment in expectations.  It’s a shift from a look back and partner with machines that look forward, use more data sources and get to analysis faster.

If you have any examples of success or any challenges I’d love to hear about them.

[i] Mike Hogan, “big Data of your Own,” August 2013, www.factiva.com

John Adams, “Be careful or Big Data could Bury your Bank,” January 25, 2013 http://www.factiva.com

Retail impacted by digital finally changing business models


Supply chain software, and a minority stake at that, wrote Loretta Chao to WSJ readers made it clear that Nordstrom definitely is intent on preserving their advantages.  As a retailer, they definitely get what digital business means–they are actively engaged in shifting distribution and inventory control, not merely adding data points to track, but redirecting their fulfillment.

Yesterday, the Wall Street Journal also reported shifting focus by big mall developers, who have leveled the mall spots once anchored by top retailers to make room for a new wave of experience magnet attractions. Fewer and fewer people respond to traditional retailer marketing and sales cycles.  Ron Johnson’s early insight that shoppers were ready for greater transparency was ineffectively translated and instead of turning JCPenny’s into a winner, he managed to accelerate its decline.

In a 2013 blog post following a peer discussion of this strategic failure, I wrote:

“The days in which stores stood between buyers and consumer good manufacturers are dwindling. Location or proximity to the consumer may still have an edge but your competition’s ability  to insert themselves into the face to face transaction has dramatically altered the sales dynamic. Mobile communication devices  make it easy for sellers to find buyers anywhere anytime; and yet, the playbook  for many stores , from department stores to specialty retailers,  fail to keep pace with the change in buyer behavior, perception and thus fail to live up to  increased expectations.”

(Click the link for the full post:  For JC Penney and Ron Johnson experience counts, but which one will deliver growth? )

The realization of end-to-end digital retailing has been slow to arrive. True to form, it has not materialized evenly. The latency, or the time interval that separates store buyers’ pre-order of seasonal merchandise, and its staged manufacture, delivery to warehouses and distribution centers before making it to the store created more than one headache for retailer. In a stable environment, where information was as limited as resources , retailers may have been better at holding customer’s captive and thus been more effective in their ability to  forecast, price, track and sell in keeping with customer demand.  The once innovation of a sale to prime the pump, by Ron Johnson’s time had become a fixture in the sales cycle.

Was it really Amazon who introduced the idea of “Drop shipping?” No, as far as I know, Amazon merely managed to take advantage of Chris Anderson‘s description of Long tail distributions as it applies to supply and demand on the internet.  Amazon’s platform that made it easier for interested buyers to find a supplier no matter how rare or plentiful the good. In other words, Amazon freed consumers from the restraints of retailers merchandising and elaborate distribution schemes.

clip_image002Drop Shipping Loretta Chao explains doesn’t merely reduce retailer’s inventory storage and management costs.  Instead it enables retailers to reinvent their old process for securing product and putting it in the hands of consumers. This lets them compete directly with e-commerce players like Amazon and gain the same, if not greater advantage than Amazon’s platform provides.

Personally, I’m just really excited about what else will emerge, and realizing that DropShipping is just one element of the changes that are here but just not evenly distributed. For example, remember why Kickstarter exists? On one hand it represents the unshackling of constraints forced by manufacturers who limited what designs made it to the mass market.  New designers share their idea and get people to pre-pay and pre-order which makes it possible for more alternative goods making it into production.  The presumption of scale still embedded into the calculations that the manufacturers would need a minimum order to make production worthwhile.

Democratizing design is one thing, but imagine a non-inventory business model, one that puts goods in the hands of consumers faster with more control and choice.I recently heard a panel entitled Rethinking the Design Process at a thoght leader summit sponsored by soho house, Samsung and surface magazine, entitled Intersection 2016. Scott Wilson , original maker of MNML design, spoke with Charles Adler (founder of Kickstarter), Jesse Harrington , designer at Autodesk and Dean DiSimone , creator of Othr dedicated to minimizing the environmental footprint of remote manufacturing.

Direct to consumer, suggests that retail as it has existed for the last few centuries is finally catching up to technology, are at least some retailers. If you want to see who, check the panelists recommended you look at the following: Rapha –a completely different sales model; Tesla back to the pre-order and customize and personalized delivery; and finally Story–who boasts “Point of view of a Magazine,Changes like a Gallery, Sells things like a Store.”

If you have any other evidence of the shift, I’d love to hear about them.

 

Refreshing Core Values


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Remember the  expression built to last? It was an expression that my grandparents used to differntiate value.  What I saw as an old tool, or piece of basic furniture or clothing they valued.  The phrase also describes capabilities and inherent qualities that stand up, endure over time surviving changing conditions.

The ups and downs of the stock market represent value differently. Analysts love to pounce on companies when they stumble. The bigger the company the better the blunder and the better for the Bears.  Retail food and department stores currently appear to be under heavy fire these days, even brands and companies that dominated their industry.

So what value should you seek? Investors seek returns but don’t always consider the long term costs, do they? Does sustainability really matter?

I suspect some of these thoughts  led Jim Collins and Jerry Porras to title their 1994 book Built to Last (BTL). Sure they may have thought to follow the example and success path set by Tom Peters and Robert Waterman  whose titled 1982 research project  In search of Excellence also became a best seller.

Sadly, in writing the book Collins and Porras did what other well-meaning authors do. They put a priority on pithy copy over substantive analysis. In short, they wrote great stories.  In fact they went so far as to feature the CEO as leader/hero.  Their research (see sidebar) to distill what made companies visionary  was refashioned into a great read.  Nothing wrong with a great read, unless the reader confuses the story for prescriptive advice and your analysis turns out to be a bit superficial.  If you think I’m being harsh, consider these comments:

Martin Maneker, Collins and Porras publisher put it this way in the Daily Beast in 2009

“the heart of the Good to Great philosophy is that disciplined people, engaged in disciplined thought and taking disciplined action, have the greatest chance at success.”

Or in Collins own words on his website  posted in May 2009 about his book Why the Mighty Fall :

“[Porras and I were ]discussing the possibility of a project on corporate decline, in part because some of the great companies we’d profiled in the books Good to Great and Built to Last had subsequently lost their positions of prominence. On one level this fact didn’t cause much angst; just because a company falls doesn’t invalidate what we can learn by studying that company when it was at its historical best.”

Or Consider  Fast Company’s look at BTL 10 years post publication written in 2004:

“ at least 7 of BTL‘s original 18 companies have stumbled (8 if you’re cynical about HP) — scarcely better than the results you’d get by flipping a coin.”

In other words, the fundamentals that stand the test of time more likely due to discipline or luck. Sorry that it’s not the five that Collins and Porras research efforts describe.

So why did Jennifer Reingold and Ryan Underwood in their Fast Company retrospective review of this highly influential business book try to salvage its essence? For the same reason that these books continue to inspire and continue to be best sellers.  The Fast Company authors looked beyond the company profiles and focused on the stated principles.

As pointed out earlier, Collins and Porras in later editions had to qualify their original findings in the preface. Collins’ later writing also back pedals with post mortems describing how his BTL companies had lost their way.

I’m not the first to question the relevance of the principles to demonstrate the thesis of the book. In fact Collins was well aware of the criticisms leveled at Peters research, and why they adopted matched pair design for their own research.

What bothers me is how story telling hijacked the writers’ judgment.  For example, why use distinctive new prose when citing the principles?  The better to make believers and best sellers, that’s why.

Long before social media, Collins understood the power of language. Catchy language could  impress the ideas on his reader but also fuel fan sales, and  “word of mouth.”  Consider one of his most famous original phrasings:

“A Big Hairy Audacious Goal, or BHAG, a long-term vision that is supposed to be so daring in its scope as to seem impossible. “

It’s in these language choices that I begin to feel the book tilt.  BHAGs  conjure really ugly images.  Who, other than a hero, would dare to take on something ugly? Personally, my criticisms side with Reingold and Underwood.  Even by 2004, the BTL principles seemed less relevant in the face of massive consolidation, global outsourcing or even disruption that shifted the business environment.  But the descriptive principles they coined failed to capture the essence of deeper qualities that underlay any organizations success, ones my grandparents would recognize.  I’m talking about  people believing in people.

Recently, I attended a local meeting of the Private Directors Association. I heard a panel of three CEOS talk about their 100 year old companies.

At the close, each of the CEOs identified factors they thought helped them survive. Profitability never made their list, nor did any pithy phrases tumble from their lips.  The single repeated understanding described their commitment to people and values.  Not only have these companies experienced low employee turnover over the life of the company, they shared unusual views about proper compensation and invested heavily in training.  For two of the three, visible diversity on their boards had been a conscious decision in the most recent period.

Another notable common thread described their recognition of business value–that goods and services they offered should always exceed the price customers paid.

Pride of ownership too dominated  and was demonstrably evident in each of these companies successes though  Mead&Hunt now employee owned and operated, and the other two remain family owned and operated.  Each and every company pointed out their expectation of modest returns and willing attitudes toward change and adaptation.

In other words, missing from the conversation was the idea that any of them expected to use the business as a vehicle for generating great wealth.

A friend pointed out that mid-market company values, at least evident in the mid-west,  don’t seem to match those of corporate America.  I wouldn’t go that far. Particularly since these companies were all privately owned, its difficult to measure them using the criteria that BTL employed– 10x returns on stock price.  Not a one would be considered leaders in their industry.  Even Mead & Hunt which is employee owned understands that returns on their own capital rely directly on production and interaction with customers and not financial shell games.

Kevin Boyle, the CEO of Schulze & Burch, “the biggest baker of toasted pastries in the US” typified the distinctive attitude of these companies.  Here’s how he answered an investment banker’s inquiry about how  growing valuations and M&A affected his business.   “Keep doing what you’re doing,” Boyle said, “it’s good for me and keeps my cost of capital down, and also minimizes my competition.”

Had to laugh at that.

If you are curious Wikipedia’s list of the oldest  surviving companies found many that began before 1300  and not surprisingly they were primarily service businesses, and remain small– as in less than 300 employees.  This list https://en.wikipedia.org/wiki/List_of_oldest_companies

Pushing 60, McDonalds needs more reinvention than its latest face lift


Successful change initiatives often result from a deeper understanding of the problem than the questions that initially emerge when something that should work doesn’t.

For example, Does McDonald’s need an activist investor? This question posed by Parke Shall  today suggests McDonald’s may be in need of a more in-depth analysis. One that   looks beyond the basic data level and requires capabilities and alternative perspectives than those currently at the helm . This deeper thinking would take stock, examine the array of assets tangible and intangible as well as the various factors or flows in order to depict the present working dynamics that produce the present situation. For example, the following conceptual view by Donnella Meadows  and her corresponding outline of effective leverage points offers one such perspective.

State of the System

From Meadow’s perspective, data happens to be one of the least effective leverage points and big data is no exception.  After all data alone merely describes what is, was,  or what may result when applying particular assumptions.

Parke Shall isn’t the only one wondering what McDonald’s can do to appease its investors after a year of declining sales. The complexity of managing and formulating strategy have proven difficult for the chain whose market capitalization and earnings exceed those of several small nations.  It’s precisely why internal decision-making and long standing alliances may require more leverage points and even the most effective in changing outcomes a complete paradigm shift.

I’m Not Lovin' Itif it were up to a few active social media savvy shareholder and mommy bloggers, the changes begin with focusing less on appealing to children’ts natural weaknesses and interests.  When the executives got caught up denying that Ronald McDonald’s visits schools only to recall seeing him present, she had to ask a question that resonates with analysts and shareholders alike:

Are the executives at McDonald’s completely out of touch with reality?

It’s just one of a series of signs that suggest the leadership team and operating  executives appear trapped.  Their understanding and sense of how to make necessary changes that may put  their business on a more positive, sustainable path seems to be stuck in time and experience that no longer resembles the present or the future.

The signs

Millenial challenges reported by the Wall Street Journal in August 2014 tops the list of signs that McDonald’s seems to have lost its relevancy with a key demographic.  Ad Age reported that among Millenials McDonald’s didn’t even make it into the top 10 list of restaurants, though overall they remain the #1 fast food chain. For millenials eating patterns wsj 2014McDonald’s there’s significant impact not only across their 35,000-plus global locations, but its flat or falling sales of the past year for restaurants open at least 13 months, this hurts the US hardest where 40% of its locations exist.

Current CEO Don Thompson replaced the head of the US division effective October 15 with Mike Andres who in turn made additional changes in  the structure and leadership across the US.  The hiring announcement included appointing a new CMO and adding its first customer experience officer who quickly began to  usher new changes for the brand.  Beginning with Leo Burnett assuming their advertising responsibilities and refreshing a popular campaign.  Will these changes and renewed focus prove  significant  enough?  Today’s “lovin it” campaign launch hopes to earn back customers  and promote more positivity. 

Another traditional leverage point , McDonald’s long term relationships with key suppliers enabled mutual growth with product consistency and exclusivity.  Coca Cola, for example, has been a critical partner since 1955.  New York Times reported Coke’s contributions to a variety of successful promotions and innovations  McDonald’s introduced over the years, the smoothie being the latest example.   To what extent will suppliers participate in the extensive reinvention process? Given that Coca Cola has seemed to hit a sugar speed bump itself , this approach may be less advantageous.

This bring us to innovation at the menu level brings.  Widely acknowledged to prove challenging, the menu creep  throws off the rhythm of prep and compromises serve time, a key management metric and contributor to McDonald’s overall value proposition.  Expanding offerings such as  McCafe and McWraps, along with efforts to rebrand and position itself as more upscale may appease some consumers, but not clear these additions delivered sufficiently to slow if not deflect the falling sales.

Is McDonald’s too entrenched in the trappings of it’s 59-year old brand strategy?

The amount of  data  and analysts working on this task doesn’t identify a source or clear evidence of higher level strategic thinking.  A 2012  Booz & Company case study of Wendy’s strategy noted McDonald’s had sewn up three key competitive advantages. Brand name recognition for the golden Arches holds an enviable 88% visibility internationally, which helps it win over price-sensitive consumers who also focus primarily on convenience.

Its US location density  places a McDonalds franchise at the very least within 100 miles of every consumer.  This limits acheiving new growth by adding new outlets. It may be why McDonald’s has increased its innovation capabilities beyond what the Huffington Post reported in 2011 were evident in its Romeoville innovation center where it develops, borrows and systematizes operations innovation.  This effort enviable to most corporations prototyped the extensive experience facelifts ranging from re-architecture and mobile ordering.  Still not clear there’s enough in the pipeline to turn the tide against   longer term trends of lost relevance and eroding sales signals.

Among 32,000 consumer reports subscribers, McDonald’s hamburgers came in last when judged for its taste against 20 rivals. This suggests that it’s not just the millenials who no longer find the fast food’s burger offerings appealing, thoguh burgers and shakes continue to draw crowds to other fast casual restaurants at higher price points too.

Bigmac sticker shock Fortune 2014The problem of sticker shock doesn’t impact Chipotle or other restaurants among the ever increasing fast casual segment, but it sure has hurt McDonald’s. As Fortune reported, the growing gap between the dollar menu and higher price points continues to widen making the higher priced items less attractive.

Changes to help the struggling chain regain its growth may require either  McDonald’s board and.or its CEO to resolve deeper structural challenges characteristic of complexity.   It will require some serious assumption busting, re-framing of the definitions of success and aligning more attributes with those characteristic of open systems environment.  No pun intended.  I do believe ramping up prototyping activities in Romeoville and  live testing of customization such as those in sourthern California will also help.

The evident discrepancy between McDonald’s goals and its shrinking share of the markets in which it operates doesn’t only create unease among its various stakeholders (e.g. customers, employees, its board and shareholders. This contrary indicators also reflect the inter-related operating decisions that constrain and limit opportunity while at the same time provide effective command and control that enhance efficiency but at increasing opportunity cost vis a vis growth.  Some of these indicators affect competitors as well as suppliers,  impacting factors that compete and complement American eating attitudes and behaviors.

For example, notice the changes in attitude reported  over the last nine years by International Food Information Council (IFIC) Foundation’s “2014 Food & Health Survey: Consumer Attitudes toward Food Safety, Nutrition & Health.”

Healthy food attitudes surveyed

This data merely exemplifies the changes in attitude over time and supports or disputes assumptionsin evidence by decision-makers running McDonalds.  It also shows how little the major facelift and experience initiatives matched, let alone change pre-existing attitudes about McDonald’s on items  corresponding to what Booz *company reported as core strengths for the brand.

These attitudes are not independent of each other and reinvention will require exercising leverage that cuts much more deeply than switching out leadership and introducing additional menu changes.   In other words, the complex tasks associated with increasing growth will require fundamentally different approaches than those available to smaller competitors or innovators carving out new space and creating  new categories.  Will their investors be patient and have enough confidence to believe in their existing leadership, only time will tell.

Connecting and mobility simplifies dealmaking , are you #GivingTuesday


midia impact on social friday 2014

As reported this afternoon by the WSJ, Black Friday is in full swing. Holiday shoppers and retailers actively engage in dealmaking. The decisions elaborated supported by a web of connectivity, funneling information to promote and identify where to find the best buy on what.  The sights and sounds of the season all tweaked to arouse an emotional frenzy. Its a season preoccupied with comparing, connecting and strategic advantage worked by both buyers and sellers.

This commercial frenzy reaches another peak the Monday after Thanksgiving when Cyber Monday redirects consumers to connect online. Last year, emarketer reported that the single day figures represented 5.8% of total US retail sales for the year. (See http://www.emarketer.com/Article/Total-US-Retail-Sales-Top-3645-Trillion-2013-Outpace-GDP-Growth/1010756 )

Givingtuesday.org

#givingTuesday Campaign

The latest addition #GivingTuesday, with its twitter hashtag of the same name , launched by the 92nd St Y and the United Nations Foundation wanted to kick off the giving season with a different message. With less than one month notice, the 2012 campaign offered a charitable answer to the intensity of focus on retail shopping. By its own acclaim, the campaign quickly launched “a global movement engaging over 10,000 organizations worldwide.”

According to The NonProfit Times, donations on #GivingTuesday in 2013 amounted to $32.33 million processed on five online platforms: Blackbaud, PayPal, Razoo, Network for Good and DonorPerfect. Blackbaud, which handles contributions for large nonprofits, reported that it processed $19.2 million in online donations on the day, a 90% increase over the prior year. Blackbaud also reported the average donation it processed rose by 40% in 2013 to $142 from $102 in 2012.

As USA today further reported, “The dollar amounts and the digital evidence are impressive, but the real story is about how people are giving back,” said Kathy Calvin, CEO and president of UN Foundation, a #GivingTuesday founding partner.

Has #GivingTuesday started the important international conversation about caring that Henry Timms, the originator and executive director of the 92n Stree Y hoped?

You bet it has. A quick look at the numbers indicates significant coalescing attention and energy that goes into #Giving Tuesday literally pays off. Figures from Emarketing news and the Department of commerce showed total usRetail sales for 2013 reached $4.53 Trillion of which Mobile commerce represented only $42.13Billion, an order of magnitude less. Just zeroing in on Black Friday and Cyber Monday Adam Marchick writing last week for internetretailer.com showed that smartphones and tablets combined drove a new record of $259 million and $419 million in online sales respectively.

Since many of the contributions for #Giving Tuesday were mobile, there’s significance in collecting $32.33 million, or 12.5% of the commercial online sales activity achieved on Cyber Monday.

Current e-commerce statistics from Statista state that “40 percent of worldwide internet users have bought products or goods online via desktop, mobile, tablet or other online devices. This amounts to more than 1 billion online buyers and is projected to continuously grow. “ The clear influence and  power of connection made simpler with mobility continues to surprise and challenge the best of plans for resource allocations.

The  ability to make changes in the world will continue to reside in the power of greater connections. How they get put to work and for what collective end, remains at the moment within our reach. Don’t just cross your fingers but use your own connective power to shout out to your friends #Giving Tuesday opportunities and help move the needle on donations every upward. .

Successful businesses both Create and Capture value, Can you?


A year ago,  Casey Winters then data analytics guru at Grub Hub, shared the data analytic tools that Grub Hub found contributed value to improving long buy-cycle results.  His list of dominant vendors who then weren’t cutting it made me wonder what tools he found most useful now.  Casey  has since moved on to Pinterest, to further the message its CEO recently sent about its power to create beauty and creativity not merely provide social bookmarking. Double congratulations seemed to be the right tone for my note for landing the job and completing his Chicago Booth MBA.  I wondered whether Casey credits his experience at Grub Hub or his analytic experience coupled with his concurrent studies at Chicago Booth to his greater understanding and usage of predictive analytics?  Before asking, I found myself distracted by content in Casey’s tweet stream, especially a story he found akin to GrubHub’s experience–a start-up that had launched in 30 cities in 6 months.

Casey reminded me what value exactly analysis delivers.  Sure, telling stories grabs headlines and has a way of rippling to the very combination of people responsible for business growth.  I’m not just talking investors, but sexy company stories draw employees and on the web, links make it easy for customers to find you too.  Increasingly the value created in the data streams seemed to be secondary to the primary business operations.  Google in sharing the under the hood analytics understands the mutual value creation venture and so do a great many others in the tool creation business.  But that’s just the beginning. Value may be created but unless you capture it then your business won’t last very long.  At least that’s what a number of successful investors track.

Patterns

Sure, start-up fever seems to infect everyone today.  We love stories about founders who go from nothing to something based on their own grit and determination.  Sound familiar?  This quintessential bootstrapping myth  fuels American’s reverence for business. The reincarnation of Horatio Alger stories as rags to riches tales, applaud individuals who by their own hand pull themselves up. In fact, the origins of the term boot-strapping comes from the idea that regardless of one’s background, you too can create a livelihood and viable business from scratch. Adora Cheung’s startup  recently named San Francisco startup of the year story follows this pattern.

Of personal interest, are the patterns that emerge from both Adora’s story and that of Casey Winter.  Both of them developed an expertise acquiring online users and retaining them, a key growth driver for any business. I suggest that they not only understand how to create value, but their skills bring critical value.  What advantage does a web-based business at least for now, have over on premise businesses? The ability to focus on the behavior of the end users, find patterns and then build profiles that allow them to tweak the site to improve not the data analysis capture but convert the information into tangible financial benefits.

“They’re focused on optimizing everything,” said [Michael] Hirschland, adding that its systems allow it to be far more data-driven than its peers. It’s already using data to predict where best to expand beyond city centers, into the suburbs.

 

Admittedly, simple businesses make it easier to focus on the few moving parts at once and understand what works.  Long buy-cycles tend to show more complex business decisions, where the co-dependencies may lie beyond the control of the user your connections allow you to observe.  Both Casey and Adora honed their experience analyzing  businesses appealing to  simple users direct needs. This no doubt helped them increase the contribution value of their analysis, make insights easier to uncover and use them to move their businesses to greater advantage by exploiting opportunities beyond simplifying their users’ on site journey.As they accumulated additional perspectives of happy online users and recommended tweaks to improve the ease of their site’s use they took a slight turn.

human advantageNaturally we compare and contrast personal and experiences, and no doubt Casey and Adora compare and contrasted their personal site experiences to wider systems of experience.  They exercised these skills to leverage the value created by their analysis and tools and explore using them to optimize offline services.  These associative connections remain outside the realm of predictive algorithms and require human know-how.  This level of strategic thinking allows a business to scale and in their case replicate  in multiple locations quickly.

The analytics know-how does more than create value, it offers the advantage that comes from capturing the value too.

The value chain break down

Let’s face it,our brains are wired to find short cuts.  Anything that saves us from thinking about a routine action allows us time and energy for other things.  A mobile app spares us from having to remember the URL, or type it accurately into our smart phones and access the information we want quickly.  Why should we have to think about basic things when there’s an app that captures the necessary information and simplifies if not eliminate s the guesswork for a host of activities.  That’s what GrubHub did and that’s what Homejoy does online, though it might want to merge with  HouseCall.

Simply put, the reason businesses must be online, happens to be why everyone realized the value Facebook or Twitter offered–a connected, concentrated user community.  Decades ago, businesses opened in the mall for the same reason, be where your customers will find you.  Search engines remain important but increasingly they take second place to an established phone app.  Each tool creates value but they capture value very differently. Snaring customers may be the first step, but mobile apps done well allow you to keep them–one of the fundamental drivers of growth.

Websites when linked to effective traffic directing vehicles has been the principles fueling and giving new life to direct marketing analytic firms for a long time.  Today, successful analysis of logistics matters.  What steps a business takes to simplify real world experiences certainly creates value, but the trick again is to capture it.  A host of online tools exist to make it a snap for users to find, pay for and track the delivery of  what they need.

There’s evidence that Jeff Bezos understood this from the beginning and increasingly stock analysts ascribe greater value to Amazon’s combined capabilities over its narrow profit margins.

Today, Amazon  offers its users one stop search, payment and delivery platforms. The early versions of online e-commerce focused on one aspect of business, displacing if not eliminating the middle man by competing on price that squeezed  the markup between wholesale and retail. Amazon’s  logistics expertise and value capture to date make it a significant threat but will this advantage sufficiently keep them winning over other retailers?

The array of sensors residing in smartphones no longer tip the advantage to online service providers.  These changes impact how everyone in the ecosystem accesses the data, and gets meaningful information from the various readings, like Geo-location, gyroscope, accelerometer, or even the magnetic flux. In the near term,  smaller service business like Grubhub, Pinterest and HomeJoy are deriving benefit from mastering logistics.

For each business the advantages go beyond match making and into literal service management for both consumers and suppliers/providers.  That’s the beauty behind HomeJoy.com.  Consumers  find qualified, cheaper house-cleaning services, and the cleaners benefit from vastly improved wages, simplified scheduling help and timely payments.  If that’s not logistics than I don’t know what else to call it.

None of these were businesses that followed the simple pattern representation of “If you build it they will come.”  The article details can fill you in and tell the story better. so, do take a look:

Summary

What’s the key to creating and capturing value? Here are three suggestions.
1. Mine the Gaps
It’s not about whether your business plan happens to online or on premises.  Can you find gaps between value created and its full capture, aka system level inefficiencies?  I urge clients to look for areas where one or more parties in a transaction leave money on the table.  In the case of HomeJoy, Adora and her brother didn’t seek to create a cleaning service, they merely reflected on their own experiences and applied their knowledge of logistics to realize that the home cleaning service business suffered from inefficiencies they could exploit.
The Gap:  Established cleaning companies were prohibitively expensive.  At the other end of the home cleaning market classified or posted ads for cleaners  were unknown entities.  Users face a choice between paying prices that prohibit frequent purchase of “qualified cleaners, ”  or hiring unknown, self-qualified cleaners at more affordable prices, with little or no recourse if the service proves unsatisfying.
The system level inefficiencies suggested that if they could resolve these issues, they could easily scale the business to become an established cleaning company.  No HomeJoy was doing nothing to disrupt the market, they merely used their ability to mine and funnel the knowledge within the system for greater efficiency.
2. Chicken or egg
What you don’t know makes it harder to understand where to start.  Both Casey and Adora and even Jeff Bezos leveraged what others know, but couldn’t put to work for their own benefit. The know-how necessary for success generally exceeds what’s available in a book or published article.  Few successes come to us from merely reading it, we need to try it out and integrate it with what our experiences have already informed us.  Instead find ways to learn directly from your competition, study from the inside as much as possible. (Of course this can be very challenging to do, as Adora can attest).
Surprise, this same chicken and egg problem often makes it hard for  other players in the system.  For example, consumers often need help finding what they want, and suppliers need help finding customers.  That’s why  focus groups often falls short.  The insights may be sufficient to get you past your current obstacle but won’t necessarily offer you competitive advantages that come when you challenge and improve opportunities at the higher systemic level.  You will learn more about the issue, but the difference between success and failure comes from really finding where the untapped value lies.  In these cases the business benefited from focusing on logistics and using analytic tools that weren’t only monitoring and tracking observable patterns. .
3.  Give to Get
  Many start-ups start by thinking they will give something away for free, but you can’t give away your service and then turn around and ask for payment later.  In the case of HomeJoy they used simple old-school growth hacking tricks–printed flyers and compelling copy wasn’t hard but unless people read them they would have no customers.  So they used the advantage of satisfying an immediate need within a concentrated geography to get their message out. They passed out free water with their flyers and sure enough they built their initial customer base and then their site analytics and the web tools to help these customers share with their friends their satisfaction and grow their business.
4. Research, research, research
Matching software may be the basic kernel of value for which many real services or products depend on the web to help coördinate or connect them to their users located anywhere.  Throw in a rating system  for the service/product and now the site itself creates value, right?  But a host of very established sites such as yelp address these needs and yet both Homejoy and Grubhub are growing and co-exist with the search engines and rating sites.
The razor-thin operating margins underly the basic business models for all of these online businesses, whether you are talking about Amazon, Grubhub or Homejoy.  Created value alone won’t keep them afloat.  Each and every one of these businesses must capture that value and they did it by replicating the model. For Grubhub and Homejoy they quickly expanded to multiple markets.  Amazon used their integrated book sales systems to sell other long shelf-life products, then their excess server capacity to offer retailers online commerce  and increasingly are moving into perishables.
If you are incorporating analytics in your business, at what level of the system are you applying the insights you learn? Investing in strategic thinking can go a long way to sustain your business and insure you capture the value you create. 

Create value by sticking to principles and collaborating


I’ve been reading and writing a lot about creating value.  Value creation is what sustains our spirits as well as insuring us a livelihood. It preserves quality in our relationships as well as justifying our existence.

Does creating “shared value” accomplish the same thing?  creating value

A recent headline in the Financial Times challenged the premise of Michael Porter and Mark Kramer’s ideas on creating shared values caught my attention.  Corporate Shared Value, (CSV) conceptually seeks to align social impact and company success.  A very noble goal, akin to what John Mackey, the CEO of whole foods describes as Conscious Capitalism.  Andrew Crane’s Financial Times article merely wishes the CSV theory found its way into execution and not corporate report window dressing and lip service.

15 years ago, Frederick F. Reichheld  and Thomas Teal working for Bain Capital discovered that too few growth strategies successfully drove profits and explained competitive advantage. Since the traditional profit drivers failed to explain the discrepancy in performance, they turned to study costs.  Their research delved into a firm’s relationship between customer duration and its cash flow  and found the relationship also differentiated advantage. As they had eliminated one metric after another their discovery proved that value starts with building loyalty, growth follows and then profits result. Dual loyalty, they explained isn’t merely the reciprocal relationship between a firm’s leadership and its customers.  The duality extends to employees and includes relationships with investors.The Loyalty Effect: The Hidden Force Behind Growth, Profits, and Lasting Value published in 2001, detailed this research.  For businesses to focus and sustain this value creation process, the authors recognized would require fundamental changes in business practices including new ownership structures.

Porter and Kramer’s CSV theory in part recognizes a similar fundamental shift in business practices.  Their focus seeks to compensate for the historic failure of accounting balance sheets to report and record shared value as an asset.  Is it an output, or is Shared Value part of a  larger social movement?

Mark Cheng, Director of Ashoka UK and Ashoka’s senior advisor on social finance  explains the challenges in this article that appeared in Forbes, How Philanthropists And Investors Can Work Together To Create Social Change. He suggests, that trying to build a social innovation isn’t a company but a social movement and that’s why it requires very different investments.

To change consumer behavior whether you plan to build a new market or a social movement requires organizations to earn people’s loyalty to principles.  Reichhold and Teal explain these learnings as necessary to properly differentiate between creating measurable value and creating profits.  Porter and Kramer hope businesses will value social progress, but this alone won’t re-legitimize a business. A verbal commitment to value can’t create the cost-benefit advantages necessary to sustain the firm.

Social forces of loyalty can and often do bind customers, employees and investors. Indeed they serve as measures of  cash flow and indicate a company’s ability to deliver superior value. The interlocking set of a firm’s operating principles creates both a cause and effect which satisfies, inspires and engages all stakeholders to sustain the firm.

Alternatively, a collective solution and collaborative mindset that aligns around a broader set of principles or values clearly stated presents an opportunity to create shared value. Because the concept of shared value offers people the means to take part with the resources of a firm, these mechanisms also share in, and contribute to, the success of the wider social movement.

Cheng explains that different funders should rightly have different roles.  A social business partnership between a business enterprise and an NGO doesn’t have to compromise or tradeoff its economic goals for the benefit of social good.  Using philanthropic funds to cover start-up costs for the shared venture and utilizing the distribution prowess of the corporate entity is one way to make win-win social impact possible.

Social progress is difficult to achieve by a single player, however a shared operating model based on sound principles can be adopted and replicated to spread the changes more widely.  The goal for the business may be self-interest,  where self-preservation will be a result of its underlying value creation principles and relationships.

Markets naturally close loops and collapse, can you keep them open?


The more the more

Concepts of interdependent interactions

The current theory about the nature of our universe describes an ever-expanding system.

The Sloan Digital Sky Survey describes the three possibilities pictured on the right as follows.

  • Open, suggests that the universe will expand forever
  • Flat, the universe will also expand forever, but at a rate slowing to zero after an infinite amount of time.
  • Closed, the universe will eventually stop expanding and recollapse on itself,

These possibilities also apply to the concepts of markets, cultures and geography. Yes, I said geography and it is your sense of doubt that both interests me and is the subject of this post.

Life on the Frontier

Ongoing expansion, what I like to call the more the more can be difficult to see; principally because  we recognize boundaries before we understand the opportunity.  What we know doesn’t come to exhaust what’s knowable and often great opportunities present by pushing forward into the unknowable realm. For example, the concept of reproduction naturally creates many from one, ideas too, tend to generate more ideas, one event spawns multiple stories. So why does our mind resist the concept of the more the  more so earnestly?  You did, didn’t you?  In each example, your mind naturally generated the counter case or qualifications that challenge basic beliefs in loose conceptions such as the more the more. Don’t get me wrong, edges prove very useful. Knowing the beginning or that the end is at hand helps, and the more the more merely builds on that realization.

Inability to see an idea’s validity doesn’t preclude its existence.  New concepts find their way into our web of understanding; however more often they are quickly  buried by every day experiences that prove the contrary. Consider the construct, “the United States.” The idea finds expression in a variety of forms, separated by clear boundaries. Which popped for you?  Perhaps the United States appears in your thoughts as a very concrete physical representation such as part of the North American continent, or as an outline on a map. Neither of these describes the emotional representations conjured in the minds of a new citizen, a tourist or a terrorist.

Utility theory by contrast, attributes a root cause to the propagation phenomena that perpetuates an expectation of quid pro quo, Value for Value. I work in exchange for money that I can use to buy things. Economic principles and monetary theory captures much of the same concepts but is a poor substitute for a universal theory.

Specific, General or Generic

Our mind seamlessly associates specific, general and generic cases of a single construct into a curious looking web of meaning.  Some strands loosely connect on the periphery, while others layer more tightly together around a series of cores.  The meaning that first comes to mind, doesn’t negate the others but may need other distant cross-associations to remind us.Experience can obscure our reality

Let’s talk markets. Most of us spend a significant part of our day working, where we work, or what we do represents a market and our labor factors into the dynamics.  We also consume things, and the choices we make on which items, where and when represents our participation in other markets.  For example, urban societies prefer to cover their feet.  The look –structure and style of these coverings tend to vary by climate, activity and gender. Our mind recognizes the common linkage of the numerous names attached to the variations of these objects  that cover feet.  On this level of linkage, we may attach the same basic utility to all foot coverings. That utility takes on more definitions and attributes when we consider our attachment to our culture and desire to fit in. Do foot coverings in India equate to the usefulness of foot coverings in Brazil or New York City? I cheated just now, I interchanged usefulness with utility to help ease your mind.  To validate the more the more try suspending the first boundary you meet and search your memory banks and reach for greater understanding.

Do you feel ready to put that insight to work in your business?  To grow or better serve the marketplace, we often have to re-imagine the boundaries.

If there’s a dominant player in your market, how might redefining the market give you a bigger share?

Don’t let the edges or boundaries you see stop you from challenging the value of this  representation? You don’t have to challenge the sovereignty of the United States to recognize that there are ideas that transcend the concrete borders, and capitalizing on those may help you serve your existing  markets better and expand into new ones easily.

 

my big Data Donut


Two days in a row I managed to catch very different talks about big data, but came away with one big duh and several new insights.  In short, my prior training and experience using analytics to drive strategic decision-making placed me comfortably up the curve.  In return for my limited investment of time and attention, I gained a few new ideas, collected some cogent descriptors to share with clients and reawakened  elements in my strategic thinking process.

Big DATA , just a conjunction 

We all know Big because we know small. Everything classifies as one, when we decide it’s not the other. Big is also a euphemism for many.  Statistically, the bigger the sample, the greater it’s  significance. Bigness insures enough cases to draw general conclusions about a population.  Most of the time we don’t care about the population but we do care that a sample represents the population we care about.  An “Everyman” should be average and appear at the top of the bell curve, or normal distribution, right? Will being average, change the odds of being big or small? hold that thought.

We recognize data when we see it too. In excel, Big spreadsheets contain many rows and or many columns of stuff that we call data.

Changes in technology bring more data, we record and keep records of events that previously were not possible to record. More data gets created when instruments simplify its recording over ever smaller intervals.  For example, satellite data records and transmits continuously atmospheric particle movements,  Nike’s Fuel metrics measured by its band can provide streaming location data of people’s changing heart rate.

Put the Big together with Data along with the ease of access and you find yourself understanding Big Data coincident with the cultural shift  Big Data’s wider access produces.

If you build it they will come

In Big Data’s case, technology shifts made lots of data more accessible which increased people’s application in their decision-making.  At this hour, I can hear the helicopters hovering over the major highway junctions nearby to monitor traffic and issue the reports broadcast over radio and TV.  Everyone wants to avoid sitting in traffic, and their consumption of this information and decisions of when and which route they drive naturally impacts the pattern.  The widespread availability of GPS and map services rely on alternative information sources to generate traffic congestion maps , and influence consumer travel decisions as well.  Don’t you rely on one or more of these information sources? Why? few of us know the details behind the projection.  Instead,  we feel better with more information available, after all,  traffic information helps us avoid the inevitable–the likelihood of being stuck and delayed in rush hour.

Bottom line, consumption makes Big Data valuable. Its availability  raises questions, but we often skip the critical ones.  We ponder its use, before questioning its reliability as in what do I do with it? How can and should it impact my decisions?  

Why?

Humans’ daily actions rely on the process of cause and effect.  I turn on the faucet to make water come out.  I say “please,” you say “thank you.”  How many miles must I run to burn off the Fat calories I consumed eating a donut for breakfast?   Hmm, can I measure my fat burn rate? If I work for the donut producer, I may focus on the sales effects that result from posting this information.

These sets of  reactionary questions miss the opportunity set that Subway anticipated and took to the bank.  I don’t know the story behind Subway’s marketing strategy , haven’t looked into the chain’s profitability, but they clearly seized advantage of a trend fueling both  awareness and their revenue. They twisted the cause effect to create a successful Cause marketing campaign.

Worry about Bad not Big Data

In the second talk, Casey Winters, the head of digital marketing for a growing web-based start-up called Grub Hub spoke about the poor decisions being made using vanity metrics.  Traffic isn’t a new metric for retailers or commuters.  In business, Cost per Acquisition, Lifetime Value and Conversion rates represent a few key performance metrics that when properly calculated, effectively drive strategic investment decisions.

The challenge today isn’t their availability as much as their reliability.  More sources  of information reflect the ease with which some data can be measured.  For example, Google Analytics offers the basic traffic stats freely to any website who embeds their code.  Advertising agencies spent a decade redefining themselves to be digitally capable, and help their clients use these new tools to distribute their marketing dollars to physical and virtual locations.  The result, more data and Data Scientists emerging as guides through the complexity associated with Big Data.

STOP making Data into donuts

More data spread around doesn’t make anyone smarter, especially when not all available measurements of existing data prove trustworthy. Standards help a lot, but they may not  sufficiently help separate the noise from the signal. Don’t just use the data that’s available but be sure you understand its creation.  Take the case of the glazed donut comparisons shown above between Krispy Kreme’s Famous calculated calories to Dunkin’s Glazed donut figures.  The fact that they appear together in one chart doesn’t mean their calculations used the same computation process.  The information on its face lead to one conclusion, which may or may not support your own experience of these donuts.  Haven’t you already  put that experience to use and attributed  the observed differences’ cause to something other than the method of calculation?   In short, you used cause and effect favoring intuition over critical thinking.

When it comes to talking about strategy,  we often forget to ask the questions before we pull the data.  ROI may justify one investment choice over another and then again it may merely be used to confirm the value of your investment decisions after the fact.  Data should move you from insight to reality.  Remember a dot in one dimension is a line in another, the value of the era of big data increases our opportunity to capture more dimensions.  The challenge is using data to gain more perspective and beware of our biases.

Big 3I competencies: Why are they so darn hard to acquire?


Creating value and organic growth opportunities requires uncovering opportunities often hiding in plain sight. Innovations challenge expectations including possible returns on the effort.  We take for granted what’s under our noses even though it may be exactly where we need to pay closer attention. Understanding how perception affects our preferences makes compensation possible. Vigilance helps,  especially awareness of value on multiple dimensions. There’s a monetary aspect and there are ideas we hold near and dear.  Both values motivate human behavior and that’s what makes life interesting.  Let’s begin our exploration  looking at traditional expressions of value  after an introduction to the concept of “fundamental attribution,” or first perceptions.

Prior knowledge separates surprise from distraction.  A sudden unanticipated event will jolt our senses. Our sudden vigilant state will recede when we recognize familiar people, or cues, associated with things we know make us happy. Surprise includes circumstances or context that make us expect what comes next and so we relax our guard. The fundamental attribution idea literally draws on internal experience. Stored knowledge takes care of us, finding a fit to situations and environments we meet. That doesn’t mean we pick the best fit. Often familiar,  frequently used ideas come to mind faster. Logical or rational alternatives follow, too late to be useful. That’s where intention, pausing before reacting, offers the pre-frontal cortex time to process. This internal tradeoff makes humans wonderfully complex and predictably irrational.

The trick is to understand how circumstances get people to do what you want and avoid them blowing up in your face.  Psst, the answer goes beyond data analytic competencies, though that’s important.

Perception and preference the Big What?

Data comes in one flavor, but tastes differently to consumers than it does to product and service providers.  Everyday, more code and identifiers amplify specific and ambient details associated with activities such as tracking goods, service use etc. The convenience, cost and time savings provided by standard identifiers like bar codes, account numbers, social security numbers, email addresses and phone numbers also simplify providers, up and down the supply chain, catering to our unconscious preferences. Every day, we compromise a little more of our privacy and anonymity in the process.

The sheer volume, veracity and velocity of all this raw, “Big” data makes navigating the future possible. The tricks require exploring past and present relationships between variables. Predictive Models use that deeper understanding of variable relationships  and their interactions to create opportunities, control risk producing conditions and optimize sources of marginal profit. The results enrich our lives and few of us feel oppressed by this Business Intelligence (BI).  Big Brother does exist, but so does Big Sister, Big Doctor, Best Friend, Old Roommate, Big Pen Pal etc. In other words, government  surveillance creating the old FBI style dossiers, pales to the knowledge stored about you by your bank, Google, Facebook, Amazon and other retailers. Healthcare regulations and practices preserved the privacy of your information, and their slowed migration to electronic medical records. Their failure to keep up with the wider digital data practices have also slowed  diagnostic advances and cost saving opportunities.

Real innovations begin with insight, once the province of small tests and strictly the domain of human intelligence.  Today Big Insight crowds out the spotlight occupied by BI. Cheap storage and faster processing makes data mining possible for anyone, but it is the strategic opportunists  with the foresight to be serious players and accumulators that continue to change the world.  Recently, GigaOM  identified several use cases  while highlighting Terradata, the makers of the first terabyte scaled database. The full list is worth reading, as I mention only a few.

  1. Steve Jobs infamous statement that Apple doesn’t do customer research no longer holds true.  Terradata named Apple as its first customer to exceed a petabyte of storage. Apple rapidly accumulates  transactional information on their customers to understand customers across product groups.
  2. WalMart’s data processing and analytic capabilities go beyond simple sales efficiency. The data helps instruct and educate its suppliers with insights about packaging dimensions as well as shelf space location etc.

Intelligence to Influence requires insight

The ongoing arrival of new technologies and embedded tracking codes continue to fuel the race to understand and use real-time ambient data to influence transactions. More data makes it easier to see deeper underlying patterns more clearly.  With greater awareness, trends can be spotted and tracked more readily and the impact of different interventions tested simply and more thoroughly.

Understanding the data requires more than iterative recombination, it takes expertise. With knowledge and experience patterns can be understood by both people and machines (see Earlier post: understanding-aint-believing-and-yes-there-are-economic-consequences).  But it takes  curiosity to explore different dimensions and generate insights.  Here are two different takes:

Luis Arnal of InSitum explains what holds back many of us. Please listen to his Design Research Conference in 2011 complete  presentation, absent the charming slides. This summary doesn’t do justice to his talk, but  I wanted to share some of his key reflections and lessons on the steps to developing insights

Begin with data, or information records that represent your observations from field research. After collection, the data needs to be categorized, clustered.  Begin the analysis process using a simple scatter plot to understand the landscape or context of observations relative to the categories selected.  Using  intuition and prior knowledge, the dimensions you choose to contrast also leads to the direction in which you develop associations between the data points.  What, if any, possible connections exist?  Using imagination and creativity  lines of connection appear as  part of an effort to FIT the dots to a model.  Of course the interpretations vary. Time and patience make possible “a fidelity of meaning” and the underlying pattern comes into focus. The data’s added value  suggest patterns that slowly develop into solutions. Insights, Luis explains contain  30% Data, 30% inspiration, 30% perspiration and 10% luck.   Insights facilitate the transition from confusion to help resolve the initial problem. They are the links between what Is and What If, they help us imagine how when we don’t or can’t know.

Recent article in HBR by Thomas Davenport,  another worthwhile read, emphasizes a different set of talents and experiences.  Particularly helpful for positioning your firm is one of the closing observations about the capabilities housed within your organization and the opportunities they present.

“….their greatest opportunity to add value is not in creating reports or presentations for senior executives but in innovating with customer-facing products and processes….

LinkedIn isn’t the only company to use data scientists to generate ideas for products, features, and value-adding services. At Intuit data scientists are asked to develop insights for small-business customers and consumers and report to a new senior vice president of big data, social design, and marketing. GE is already using data science to optimize the service contracts and maintenance intervals for industrial products. Google, of course, uses data scientists to refine its core search and ad-serving algorithms. Zynga uses data scientists to optimize the game experience for both long-term engagement and revenue. Netflix created the well-known Netflix Prize, given to the data science team that developed the best way to improve the company’s movie recommendation system. The test-preparation firm Kaplan uses its data scientists to uncover effective learning strategies.”

What’s the common denominator linking Davenport and Arnal?  Both reference visual thinking or the conceptual translation of ideas into tangible representations.  Again,a  mastery difficult to acquire and beyond the bounds of computers, even those as powerful as IBM Watson. I don’t think Siri creates flow charts, but she might learn.

I did and so can and do others. When hiring for analytics teams I managed, three criteria or competencies were essential: SAS skills—statistical coding; knowledge of the business; and an ability to think through new problems. i never thought to ask someone if they could draw.  One of my teams pioneered new strategies to improve profitability.  Initially, that meant differentiating credit worthiness.  Managing the portfolio however required alternative methods to promote profitability by optimizing costs and simultaneously minimize risks.  At the time, combination of competencies we needed were rare. Above all we needed flexible thinkers to tackle complex problems  and create more sustainable solutions. We learned to bet on those who offered two of the three. In time, we came to realize that the third criteria, thinking, was one we couldn’t teach.  It became the minimum requirement. In the late 80’s, we sought out academics with  conceptual modeling experience and bypassed MBAs.  Banking wasn’t the only employers seeking these skills but we were much more flexible in hiring them.

Today, the combination of technical skills proving most valuable continue to be found among individuals who have studied complex data and demonstrate visual thinking, again not MBAs. Not all designers capabilities include assembly of a sophisticated social network analysis model, but they sure do a great job of communicating conceptual ideas tangibly.

This post began talking about value.  Should the value consumers derive match the value producers derive? Absolutely not. In business the preoccupation with return on investment makes sense for private equity focused on upside and early exit. This contrasts with Warren Buffet, who grew wealthy ” thanks to his ability to learn the value of various securities and then buy them for less, a concept at the core of value investing. “Price,” he has said, “is what you pay. Value is what you get.”

Remember the fundamental attribution concept?  Buffet’s remarks on value and his actions show how easily we mistake motive and behavior.  Companies that obsess about cost risk missing key insights.  Case in point, the recent rise and fall of JCPenney’s CEO, a man clearly familiar with the power of BIs (insight and intelligence analytics) to achieve innovation. How people interpret observed behavior matter. The more detail and the more attention to context , increases chances to uncover key actionable insights.  James Surowiecki, a notable observer of the slippery slope of over reliance on analytics, recent New Yorker column , shared comments on the widely touted and now vilified  Ron Johnson, by Mark Cohen, a former C.E.O. of Sears Canada, and now a professor at Columbia”

“In most of the retail universe, price is the most powerful motivator,” Cohen said. “This game of cat and mouse with regular, ever-changing discounts is illogical, but it’s one that lots of consumers like to play. Johnson just ignored all that.”

Conclusion?

Playing effectively with Big Data analytics requires an unusual mix of capabilities. More than sheer brute processing power, modeling, imagining and speculating requires artistic license.  Machines will find patterns of relationship quickly, but not clear they will find the direct relationship between cause and effect. The reasons and thought processes that drive the behavior, remain domains where humans excel.

Its’ hard to believe that the same analysis that led Johnson and his team to create the square fair pricing missed recognizing coupons significance to their customers. I agree with  Surowiecki, who  suggests the impact of one  fundamental attribution created a rippling effect producing one error after another. The first error made by the board in selecting Johnson, created further error by  decision-makers and Johnson himself  in choosing  to push their half-baked strategy forward prematurely.

What do you think?