Greece: Land of Economic Tragedy or Entrepreneurial Opportunity?

Would an ancient Greek playwright like Euripides have ever considered Greece’s current economic malaise a source of inspiration for a modern day Greek tragedy? Probably not. …and yet, an audience for this unwritten, modern-day Greek tragedy has surged as members of the Troika continue to relentlessly pressure Greek politicians to address their overdue financial public obligations now teetering above 170% of GDP.

One can just imagine the utter frustration that Greece’s Government VP and Foreign Minister, Evangelos Venizelos, must feel every time he updates ECB officials of Greece’s economic progress or lack thereof. At a recent ECB review meeting, Venizelos, a burly looking character, bellowed a strong opinion in the nearly empty chambers of onlookers. He told anyone who would listen that to view Greece as the “central problem” of the European and global economy was “false, dangerous, and unfair”. When I read his quote in a local paper, it sounded like the perfect opening line for a riveting and engaging modern-day Greek tragedy, whose first scene might begin as follows:

A Modern-Day Greek Tragedy
As the sun sets over the Athenian skyline, scene one begins. A spotlight, as though originating from the night sky, shines brightly upon the Acropolis. The stage is the city of Athens, while the audience is a virtual network of headline news readers who watch with great anticipation for clues on how this extraordinary Greek tragedy will unravel. 

The first scene begins with a narrator’s soliloquy on Greece’s current financial woes. In a monotone voice, he tells the audience that Greece is in debt up to its eyeballs. The country of 10 million inhabitants owes over 317.31 billion euros plus interest to European bankers and other investors, …which translates to a shared debt of over 31,731 euros per Greek citizen. With unemployment at 27.8% and almost twice as high among its youth (58%), the Greek population has a slim chance of ever paying back its creditors. Increased austerity measures have helped reduce the need for more debt but have done little to address the amount the country owes overall. The severe cut backs have made Greek everyday life exceedingly difficult by spreading public misery, triggering social unrest, encouraging talent drain, and fostering capital flight. 

In a baffled voice, the narrator turns to the audience and asks the following questions:

If austerity has truly brought the Greek people to a dead end, what can Greece’s leadership do today to help secure a better future? How can their government policymakers attract foreign direct investments, create local employment opportunities for its citizens, and eventually reignite a new and sustainable Greek economy? Are we doomed or is there hope among us?

Suddenly, the silence is broken. From the audience, a group representing the future of Greece, speaks out loud. Their message is direct. Their recommendations spot on and their intentions, genuine. They are none other than representatives of Greece’s young professionals.

A Dynamic Facilitated Discussion
Unwittingly scripted into this next scene, I arrived in Athens for a last-minute business trip earlier this year. Prior to my departure, I had asked various groups of Greek young professionals through LinkedIn and other sources to meet with me for an informal discussion. For nearly two hours, we chatted candidly about the future of their Greece.

They were an eclectic bunch, fifteen in all. They covered a wide range of backgrounds including post graduates, young entrepreneurs, teachers, and professionals working in the private sector. Many had spent time outside of Greece either studying or working internationally. For them, Athens was their home, and they had a vested interest in her future. I agreed to write an op-ed expressing their views so their collective recommendations could be read globally.

I began our facilitated discussion with a hypothetical question that went as follows:

If this Group was offered access to a 100 million euro fund to spend in any way they chose for the betterment of Greece, what would they do first and why?

The Group offered three suggestions, which together revealed some fundamental issues that go far deeper than the well-documented mistrust between Greeks and their government. First, funds should go toward changing Greece’s educational system and specifically toward the placement of more non-Greek teachers. Group members felt that the practice of recruiting teachers from the same student body had potentially fostered a myopic view among Greek academics. Bad teachers who have little fear of losing their jobs are rarely challenged by outside peers nor formally evaluated by their students for their comments and suggestions. With a strong bias towards ‘teaching to the test’, teachers have become unchallenged, while students have lost their genuine desire to learn for the sake of gaining new knowledge. To make matters worse, students are never certain if and when they will graduate as teacher and student strikes are common.

Exposed early on to disinterested teachers and unpredictable graduation dates, Greek students have developed an inherent dislike to academia. Their disdain for their educational system has resulted in a long-standing rift between industry and academia, one which has severely lessened the government’s support and industry interest in the development of Greek-based R&D initiatives.

From an early age, children are taught to aspire to public sector jobs. These jobs form part of a government promise that offers lifetime, financial security for its citizens. Aiming for a different career path is considered out of the main stream. Under these preconceived notions, entrepreneurship ranks low as a worthy career among Greek family members. They view young would-be entrepreneurs as fools rather than business pioneers. In fact the literal translation in Greek for entrepreneurship is ‘business man trying to do something’. …they just don’t know what that might be!

Not surprising, the second suggestion for the allocation of the hypothetical 100 million euros was to boost the poor image of entrepreneurs within Greek society. At first I thought the Group’s suggestion would also include financing for an entrepreneurial eco-system which might include a startup incubator and an innovation center. Instead it focused entirely on addressing the severely marred image of entrepreneurs within Greek society. Intrigued, I verified this stigma with other young Greeks I met during my trip and found that indeed it was true. They also felt like ‘social outcasts’ who preferred not to share their dreams with their respective friends and families.

Where American entrepreneurs relish the rebellious freedom associated with entrepreneurship, Greeks do not. Greeks rank social acceptance of their entrepreneurial dreams as a top priority. Not addressing this social concern first could significantly lessen the long-term effects of any experimental entrepreneurial program. Certainly much more can be read into this social angst, and I encourage readers to delve further into this discussion among their friends and colleagues to explore innovative approaches that will turn the tide of traditional thinking.

The third suggestion for the fund was expressed as an off-handed comment but nevertheless unveiled some valuable truths. To the Group funds should be spent to create a new and independent political party, one that would be open to delivering new government promises for financial security that were not associated with a position in the public sector.

A New Normal
Undoubtedly the Troika’s demands have forced layoffs and salary cutbacks within the Greek government that have jolted the fundamental foundations upon which Greek life has been based for decades. Today, a new normal is evolving between traditional Greek  family expectations for job security and government promises. Neither has experience navigating through these troubled waters and as a result blame the other for Greece’s severely weakened economy. Workers strike frequently, making matters worse, while lawmakers struggle to acquiesce to the demands of their key industry groups. Last year alone, the government published over 240 legislative reforms, which created havoc among business owners and investors who remain on the sidelines awaiting greater economic and political visibility from their government.

The Group’s Recommendations
Hanging Merkel in effigy may help release some anger among the Greek population but as the Group pointed out, there are better ways to deal with the current crisis; however, first things first. Steps to favorably reassess the role of the entrepreneur in Greek society will very likely spark a cottage service industry of business coaches, entrepreneurial therapists, web designers, mentors, and more. Their growing presence will encourage other young adults to consider entrepreneurial pursuits, while simultaneously, reverse the current ‘social outcast’ stigma associated with entrepreneurship. If supported by favorable policies and legislation, Greeks living abroad may see this initiative as their calling card to return to Greece. Their expertise, networks, and enthusiasm should further unleash the many innovative capabilities currently bottled up within the Greek population.

The Group felt Greece could one day become a low-cost solution for big data and data analytics services globally. Just as India captured the call center and IT sectors, Greece’s mathematical prowess, recognized throughout history and the world, could drive both the low end side of the business where big databases require meticulous ‘cleaning’ as well as the high-end side of the business where sophisticated algorithms for machine- to-machine communications among devices or robots are required.

Institutes for Excellence
The Group suggested the development of an independently operated Institution for Excellence or IE whose purpose would be to teach and mentor students on the educational tools and skills needed to launch a big data and data analytics eco-system, specifically a human capital engagement research center. The Institute would reside within an existing university but operate independently. Their campus presence should reignite a new sense of purpose at academic institutions, one that industry could value and be willing to support financially. The Institute would have to be fully insulated from political influence and be governed through an independent board whose members represent its constituents equitably. The IE’s footprint should be designated a tax-free zone to help students finance their startups. Startups that reach a specific threshold in sales would be spun off into the Greek economy under a gradual legislative assimilation process.

Funding for an Institute for Excellence could come from three sources. First, from Greek diaspora who may be willing to return to Greece and actively participate in a teaching/mentorship program. Second, from a modified tax amnesty program similar to one implemented in the UK where tax avoiders can come clean with their overdue tax bill by investing in qualified startups. To help Greeks make the transition to entrepreneurship, however, this tax amnesty program could be further simplified by issuing shares from a fund whose charter includes the establishment of multiple Institutes of Excellence throughout Greece and, potentially, other countries.

A third funding source would come from international private equity funds whose involvement could lead to future investments in the IEs startup companies and relevant initial public offerings or IPOs at both local and global stock exchanges.

Existing organizations such as MIT’s Venture Mentor Service ( http://vms.mit.edu/) can be tapped for guidance, know-how, and strategy. As is often the case with entrepreneurship, the initial phases for proof of concept are the most difficult, however, there is little doubt in my mind that the 15 Greek young professionals who worked through these ideas with me in less than two hours can lead this charge. If given the chance, they and their peers could offer Venizelos with another set of talking points that will change the Troika’s next discussion from one of exasperation to one of opportunity fueled by sustainable economic growth.

© 2014 Tom Kadala

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Harnessing Big Data with a Systems Thinking Approach – (A Harley Davidson Case Study)

With 90% of the world’s data created in the last two years, what can we expect our data vaults to hold two or even twenty years from now? Today we measure our lives in peta-bytes but by 2020 estimates show a 2,300% increase in the bits and bytes that will define our lives. 35 zeta-bytes to be exact. How then can we as a society leverage the intrinsic value of so much data without getting bogged down with its complexity?

Around the turn of the century, we experienced a similar moment of euphoria when retail outlets opened ‘virtual stores’ and sold products to online buyers. A famous IBM TV ad once depicted an overwhelmed young company whose products went from a few online orders a day to hundreds of thousands. In many respects we have come full circle and are back at the starting gate of yet another era of unprecedented growth only this time instead of millions of orders, the focus is on zillions of data points.

In 2000 CEOs focused primarily on IT integration and supply chain strategies to fulfill a surge of orders. Their managers implemented the latest e-commerce packages, leveraged the cloud to reduce costs, broadened and compressed their global supply chains, and trained their workforce to adapt new work flows. Success was determined from a customer’s positive experience, measured primarily by the number of accurate and timely deliveries.

Today, the paradigm has shifted away from a transaction centric one to customer centric. Companies no longer wait for customers to buy but instead develop sophisticated algorithms that can compare a specific customer’s purchase history with multiple data sets including credit rating reports, recent purchases, and most extraordinarily, their genuine propensity to buy based upon the web pages they most commonly visit. Surprisingly, web behavioral data has become a powerful data complement that can offer unprecedented efficiency benefits to both the merchant and the consumer. Customers receive compelling suggestions, while stores inventory the products their customers will most likely purchase. It’s a win-win for both. Issues of privacy remain a sticking point for some individuals, but, as the benefits to the consumer improve, even these issues are expected to become less significant.

Striking the optimal balance will be tricky especially when the journey also involves flogging through mounds of unstructured web data. One approach being talked up within academic circles is systems thinking.

MIT’s SDM Conference – (sdm.mit.edu)
At a recent Systems Design Management (SDM) conference at MIT called “A Systems Approach to Big Data: Going Beyond the Numbers”,  Senior Lecturer J. Bradley Morrison greeted a packed audience with a refresher on Systems Dynamics; the study of how all the various components within a company (people, materials, contracts, etc), for example, interact and react together to create a product or service. Morrison’s ‘Back to the Classroom’ exercise offered new insights on how the principles of ‘systems thinking’ that today help companies scale their global operations can also be applied to leverage the new era of big data. His explanation is also testimony to the incredible versatility of ‘systems thinking’ and systems design management principles.

Morrison divided ‘Systems Thinking’ into various key areas. First off was ‘Dynamic Complexity’, which evaluates reactions when a smooth-running assembly line becomes inadvertently interrupted; for example, when a supplier’s product fails and an alternative source is unavailable. According to Morrison, unexpected manufacturing events can also have a direct affect on a company’s moral and effectiveness. The reverse is also true where systems that operate smoothly can greatly improve on what Morrison refers to as the ‘Mental Model’.

Another key area is ‘Stocks and Flows’, which Morrison dubbed humorously as  ‘Bathtub Dynamics’.  Similar to balancing the water level in a bathtub with running water, systems thinking can help calibrate inflows (i.e. inventory-build up) versus outflows (i.e. sales). The depth of the bathtub is determined by a company’s internal competitive advantage. These advantages vary widely but with regards to the alignment of systems thinking with big data, Morrison focused on skills training as a key differentiator.  He highlighted his points with a case study from a US motorcycle manufacturer, Harley Davidson.

Harley Davidson Case Study
In the late ’90s, Harley Davidson implemented lean manufacturing systems throughout its operations. Management leveraged their strong union relations to encourage employee input. The response was overwhelming. After numerous meetings, participating employees elected to improve the rotor area on the shop floor. Soon new signs went up. Space allocation was optimized, and the new employee-driven initiative became a reality. Management was pleased with their progress. The improvements paid off with an increase in productivity from 70% to 94% without the need for additional floor space. All in all the project reflected a success story until a common syndrome called ‘process degradation’ set in.

Like an ambitious diet plan, the idea reached its goal only to become unsustainable thereafter. Unaddressed issues such as an understanding of who was responsible to maintain the new process wedged away the achievements. The collaborative efforts to engage and integrate the surrounding workforce were weak and gave way to a ‘do-it-yourself’, ‘if-and-when-you-can’ approach. Despite the obvious benefits, workers returned to their old habits inhibiting further progress.

Who was to blame? …management, labor, or both?

Improving productivity with limited resources is a common problem with every company. That is why CEOs leverage technology, timely intel, and training whenever and however possible. Of these three, Morrison points to training as the greatest challenge and the most commonly ignored. Even when training is available, the type of training that he recommends is not classroom-style but rather on-the-job training.

“Learning a new skill is one thing but learning how to replace one’s old habits with a new skill is quite another,” Morrison  explained. “Workers need the opportunity to ‘change their own mental model’ before the true benefits from increased productivity can be fully realized.”

According to Morrison, managers should give their workers the opportunity to learn a new system on their own terms, regardless if it requires allocating extra time during a shift or work day — even as much as 50% more time. Unless workers are given a chance to appreciate the time saving benefits on a personal level, they will more than likely return to their old habits and simply ‘add-on’ the new changes rather than adopt them for their intended benefits.

Looking ahead…
In the next few years, new skills training will involve some form of data analytics integration. As data sources swell in every part of a business, relying on a specialized team to manage the company’s data needs will become unsustainable, especially when experts tell us that big data and data analytics, done right, depend upon the seamless collaboration and exchange of data from every corner of the company. Visionary CEOs will require every employee to learn how to collect, disseminate, compare, and use data from multiple sources. Soon-to-be, ‘unsilo’ed’ departments will depend upon each other in an entirely new manner, since the data they collect will determine the value and quality of data for the rest of the company.

Just how CEOs balance this data exchange while injecting behavioral changes among their ranks will become a number one priority for years to come. …and yet will CEOs have the foresight to allow their employees to experiment with best practices on company time? As we learned from the Harley Davidson case, those leaders that do allow their employees to adopt new behavioral changes on their own terms will more than likely achieve measurable, sustainable advantages. On the other hand, those who follow the herd by, for example, hiring more data scientists to solve their data issues, may lose an unprecedented opportunity to transform their workforce. At this juncture CEOs would do better implementing a systems thinking approach today that will allow every employee to eventually become a specialized big data provider/user for the company.

© 2014 Tom Kadala

Disrupting the Banking Industry with Big Data and Data Analytics

Bankers seen sipping away the hours over client martini lunches at upscale restaurants and posh clubs are rare these days. The slump in credit demand from the global economic crisis is part to blame but so to is the absence of ‘live’ clients. Branch offices that were once community hangouts on payday look more like empty office spaces for lease. Today bank clients ‘hangout’ virtually, while doing most of their banking online. They lurk in and out web-based services unwittingly leaving behind hundreds of data points (like footprints) that when reconstructed using data analytics algorithms can accurately reveal the client’s real identity. 

At a first-of-its-kind event in Atlanta,Georgia titled, Customer Insights & Analytics in Banking Summit 2013, representatives from various forward-thinking banks and data-analytics service companies presented their combined views to a packed room of financial professionals. Organized by Data-Driven Business (datadrivenbiz.com), a US arm of FC Business Intelligence (a London-based events company), the Summit personified the past, present, and future of banking.  First, it exposed the ugly truths characteristic of a complacent banking culture mindset.  Then it highlighted the extraordinary accomplishments from early-adaptor banks, and, finally, it unveiled a fantastic prediction on how banking could potentially hold the keys to unlocking the value of social media feeds from Twitter, Facebook, and other similar web-based services.

With off-the-shelf, data analytics, software tools, bankers can gain an accurate 360 degree view of their customers on an individual basis just by matching a customer’s banking data (i.e. loans, credit card purchases, investments) with their behavioral patterns online. The technology used to integrate data sets to match behaviors with individual names has advanced remarkably, so much so, that bankers can calculate with reasonable accuracy the ‘lifetime value’ of each customer. This magical step has been demystified by over 150 vendors who specialize in the science of Digital Data Integration or DDI. DDI connects numerous disparate data sets both structured and unstructured using assigned ID numbers. Expert companies in this area include Aster (asterdata.com, a TeraData Company), Actian (actian.com), PrecisionDemand (precisiondemand.com), Convergence Consulting Group (convergenceconsultinggroup.com) and Actuate (actuate.com, a BIRT company). The principle reason bankers want to segment their customers by their future income potential is to allocate their limited resources more efficiently.

Banks that fully integrate their operational data with unstructured social media streams will become the game-changers to watch. Already the Old Florida National Bank boasts of their younger and more agile management team (under 43 years of age) who credit their surging asset growth in the past four years to their data analytics initiatives – (from USD$100m to $1.4b). Their team has the proper bank culture, mindset, and know-how to implement data analytics tools that fully capture a digitally-holistic view of their customers. By mapping where their customers spend most of their time and money, management can target more relevant and timely offerings. Targeted customers unwittingly respond with not only a buying interest but also a willingness to refer the bank to a friend or colleague. …truly a win-win for all.

SunTrust Bank, also based in Florida, uses data analytics to determine not only the location of their next branch office, but also the optimal management qualifications required to operate one of their branches. Another interesting case study came from Wells Fargo. Their data analytics team integrates thirty-two data sets (from both internal and external sources) and presents the results in a customized dashboard format to their managers company-wide. Managers use the service to make better decisions, present data on an ad-hoc basis at meetings, and self-serve their specific research interests using a number of additional data visualization tools for non-techies. The tools they use are off-the-shelf Business Intelligence or BI software packages provided by companies such as Oracle (oracle.com/BI), MicroStrategy (microstrategy.com) and Tableau (tableausoftware.com).

Servicing a more digital client-base has come with its many challenges as well as with its unexpected opportunities. For example, credit bureaus that traditionally deny 96% of consumer credit requests often reject qualified candidates. Using data analytics tools, however, banks can integrate comparative behavioral data with a candidate’s payment history and reassess their risk profile accordingly. The results would qualify more loans that would otherwise have been turned down. Other exciting ways for banks to grow revenues include working with real estate brokers. Banks can determine which of their clients is most prone to purchase a new home and pass the list on to an agent. Agents seeking better leads will more than likely recommend mortgage business back to the bank that shared their intel.

One can just imagine how many more ways bank data can play an integral part in helping companies find their most likely customers and future business. Banks already manage the transactional data in-house and are rapidly gaining the business intelligence experience needed to integrate their customer’s behavioral data and compare their profile with their peers. Under this scenario, one might wonder why any business would not want to work with a bank that not only understands their business but also delivers buying customers.

With this much real-time intel available on customers in one central location, could banks one day become the primary lead source for their business clients? Could this new normal become a significant game-changer in the banking industry?

Despite a rosy future, the business world is not waiting for banks to embrace data analytics any time soon.  Competitive trends point to a number of threats including retailers such as WalMart who will be offering banking services directly to their customers at their retail outlets.

There is also the emergence of the ‘digital wallet’, which for the time being focuses on reducing the clutter of credit cards using available smartphone technology. Eventually one company will umbrella all credit card transactions and offer global behavioral tracking intel. Pioneers on the forefront include Protean Payments (getprotean.com), a recent startup that plans to use bluetooth technology to replace card swiping at  terminals and Wallaby (https://walla.by), a company that helps cardholders maximize points earned prior to making a purchase.  There’s also Ebay’s PayPal (paypal.com), which has released a debit card concept, which it hopes will entice developers worldwide to promote their data analytics services to SMEs.

In online banking, Simple.com does not have a physical presence nor charges the customary fees that traditional banks do. In fact, they offer plenty of financial management reports and suggestions at no charge. …all online, of course. How they make money is best understood when opening an account. Simple.com new accounts cannot be opened unless one is willing to accept ‘cookies’ on their computer, a permission which releases away a user’s complete web history to a third party. Their insistence suggests that they place a greater value in a customer’s behavioral online data than they do in their banking business.

If Simple.com succeeds, could their new business model significantly change the way consumers perceive a bank’s value proposition?  Will consumers demand additional compensation for allowing access to their behavioral online data, since the data is worth more than the interest paid on deposits?

For now, banks who are looking at data analytics for the first time and wondering how and when to take the plunge should heed practical advice from experts who spoke at the event. One individual concluded that for now, those new to data analytics should start with the data they already have and use predictive findings from data analytic tools to start a conversation rather than formulate targeted recommendations.  This advice and the rapidly evolving changes in both consumer and commercial banking remind me of the famous Aesop’s Fable about the race between the tortoise and the hare. This time, however, the winner may be a third and invisible participant called ‘Big Foot’ representing Big Data and Data Analytics.

© 2013 Tom Kadala

To Byte or Not to Bite: The Myths, Realities, and Trends behind the Science of Big Data Analytics

Without data, a company would never survive in today’s global environment. With some data, it might have a fighting chance, depending upon the quality and timing of the information.  But what happens when a company has access to too much data, sometimes referred to as ‘Big Data’? Ironically, it too could go out of business even with the best technology and staff to manage it.  Why? …partly because the data’s ultimate value depends upon who interprets and communicates the recommendations to the rest of the company, a task often left to an internal employee or ‘Data Scientist’ who may be no more than a recent university graduate armed with theories and little industry practice.  

According to Dr. Jesse Harriot, the Chief Analytics Officer at Constant Contact and author of “Win with Advanced Business Analytics”, “setting up a data analytics initiative within a corporation is not a trivial endeavor”.  It requires a lot of sponsorship at the corporate level and can take a year or two before achieving a meaningful balance between the influx of web data and its collective value to the company. Harriot shared his wisdom at a recent conference in Boston titled, The Science of Marketing: Using Data & Analytics for Winning”. This power event organized by MITX, a Boston-based, non-profit trade association for the digital marketing and Internet business industry – (mitx.org), served up an impressive venue of expert panelists who shared their best practices and experiences.

Among them was a star performer, care.com, the largest online directory that connects those in need of care with care providers. Their co-founder and Chief Technology Officer, Dave Krupinski, discussed how the company uses analytics to drive all aspects of their marketing function including, attribution analyses, customer segmentation, user experience, and predictive analyses. As Krupinski explained to a packed room of 300+ professionals, “most CEOs blindly jump into ‘big data’ analytics expecting immediate returns, only to discover (and after great expense) the many intricacies required to get it right.”

Is ‘big data’ analytics really worth the trouble?

If economic times were healthier then maybe not, but with a slowing economy, companies are forced to either come up with the next differentiating product/service that will give them an extra edge over their competition or figure out better ways to surgically target likely buyers based on real-time data. But, increasingly, fickle-minded consumers whose loyalties remain largely unpredictable have made the task exceptionally challenging. …and yet, no one can blame consumers for their lack of brand loyalty when on average they are bombarded with over 500 ad messages per day.

A Typical Corporate Scenario
In a mocked up example for discussion purposes, a typical CEO hires a ‘Data Scientist’ or promotes someone from IT, after reading positive reports from companies that have boosted their sales using ‘big data’ analytics. Once budgets are allocated and a team is in place, software with funny names such as Hadoop, MapReduce, and HAWQ appear. These packages digest massive data sets (mostly unstructured data from the web) and respond quickly to complex SQL queries entered by a team operator or analyst. The output is then parsed into a more visual friendly format perhaps using expensive Business Intelligence (BI) software and when ready, shared at weekly management meetings. For this example, the meeting is adjourned without much warning. Management felt that the results from the Big Data Analytics Team were not aligned with corporate priorities, a common problem that points part of the blame on the Data Scientist’s poor understanding of managements business needs and on the CEO for not creating a comprehensive, formal data governance.

Disappointed CEOs tend to view ‘big data’ analytics as a ‘think-tank’ style department that delivers flawless dictates to the rest of the company, when in fact, ‘big data’ analytics should be a collaborative data-sharing effort among all departments.The secret of getting ‘big data’ analytics to work is less about massaging structured and unstructured data quickly behind closed doors and more about the timely reintegration of field data from every department to continually tweak predictions and outcomes.

What should a CEO do to encourage data sharing among departments?

Most department heads do not share their data with their cohorts either by choice or due to incompatibility issues.  To address this reluctance, a CEO should first explore a standardized database structure and data exchange format that would allow departments to share their data seamlessly. Next he or she should develop an incentive plan to encourage staff members to not only share their data but request data from others. The fewer restrictions imposed on inter-departmental data exchanges, the more likely, new ideas will blossom. Moreover, the positive behavioral changes in the workforce will help the data analytics team stay focused on corporate priorities. Keeping internal operations lubricated with both internal and external data analytics will boost a company’s revenues by default. This approach can lead to a passive revenue strategy that focuses more on balancing an operation guided by ‘big data’ analytics than relying on traditional consulting advice or CEO hunches.

A Five Stage Journey
I turned to a visiting professor at the Harvard Business School, Tom Davenport, to categorize the ‘big data’ analytics journey a CEO can expect to take. Davenport listed five progressive stages needed to achieve ‘big data’ competence in today’s business environment. First, there are the ‘Analytically Impaired Companies‘. These are companies that have some customer data but lack a centralized strategy to leverage its use.  Next up are the ‘Localized Analytics’. These entities outsource their data needs to companies that follow traditional marketing practices. Then come the ‘Analytical Aspiration’ types who centralize their data sources, enjoy C-level support, and operate an in-house data analytics team. At this level companies are just beginning to grapple with their ‘big data’ analytics issues. A fourth phase has been designated to ‘Analytical Companies’ who are showing some success in using data to drive their business. Finally, and at the top of the heap are the ‘Analytical Competitors’. These companies have fully integrated proven algorithms that combine unstructured web data, with reintegrate field data to seamlessly predict a specific customers expected wants and desires based on their personal past history with the company and elsewhere including the same for their closest peer group.

Most daunting to any CEO is the notion that companies ranked at Davenport’s ‘Analytical Competitors’ level can rely almost entirely on their algorithms to run their business. The indisputable outcomes dictate their level of ad spend per quarter, allocation of ads across multi-platforms, inventory levels per SKU, quality of maintenance support, head count, and so much more. At some point one might even ask what the role of management should be for a company ranked ‘Analytical Competitor’ and the talent/expertise needed to be an effective CEO in this soon-to-be, new normal.

© 2013 Tom Kadala

‘Big Data’ – Indigestion or Innovation?

With Facebook having recently logged in its billionth user, social networking has undoubtedly become the ultimate source for ‘Big Data’. Does the possession of gargantuan amounts of data provide a guarantee for success or failure? …success from getting the right information to the right person at the right time or failure from not knowing how to manage so much data?  

To get an idea what ‘Big Data’ means to Facebook, visualize a system that handles 6 million photo uploads, 160 million newsfeed stories, 5 billion realtime message exchanges, 10 billion profile photos shown, and 108 billion queries — every 30 minutes! Impressive by today’s standards, but not for long, for what is coming next, better known as the ‘Industrial Internet’ as opposed to the ‘Social Internet’, will very likely generate orders of magnitude more data than the social-driven ‘Big Data’ we have today.

Facebook vs ‘Panelbook’
For the sake of argument, let us consider a machine-version of Facebook, one that we will call ‘Panelbook’, where ‘Panel’ refers to the ‘face’ or screen used to operate a machine. At ‘Panelbook’, machines rather than people would ‘socialize’ with their fellow machines by exchanging lots of data,  24/7. For example, a smart meter in your home would collect data from your appliances and relay messages back to the manufacturing plant (i.e. GE) where more machines using algorithms to assess its condition might issue alerts to yet more machines including, perhaps, the homeowner’s smartphone. Don’t expect uploads of photos of machine-tikes in diapers any time soon on ‘Panelbook’, but you can get the point.  ‘Big Data’ in the ‘Industrial Internet’ will undoubtedly dominate ‘Big Data’ from the ‘Social Internet, a trend that CEOs and industry leaders should take close heed when allocating corporate resources.

At a recent annual technology conference called EmTech 2012, CEO’s, innovators, investors, academics, entrepreneurs, and major industry players gathered at MIT’s Media Lab to hear the industry’s thought-leaders share their best practices, comment on trends, and recommend new ideas. I felt that their various presentations on ‘Big Data’ barely scratched the surface of what potentially lies ahead. ‘Big Data’ is more than just an onslaught of information to be managed and disseminated but is also the fluid mosaic of the constantly changing faces of the Internet, its increasing number of users, and its collective implications on our growing societies.

To make some sense of  ‘Big Data’ today (indigestion or innovation), I organized four presentations from the event in a specific order to emphasize their complementary roles in the ongoing transition of ‘Big Data from ‘social’ to ‘industrial’ data. They are mission critical data, faster access to data, and organically generated data to trigger innovation.  Notice in each description how each role has influenced areas of society that have had to react to an ever growing number of new capabilities. As one might expect, these roles will continue to evolve, causing even more changes, as nothing on the Internet remains in its current state for long.

Siemens – Mission Critical Data
Leading the charge for ‘Big Data’ was none other than the CEO of Siemens Industry Sector, USA, Dr. Helmuth Ludwig who spoke of the crucial role ‘Big Data’, played with the Curiosity vessel that landed on Mars earlier this year. On the vessel are thousands of probes that monitor more probes that eventually release a signal back to NASA’s base station where receiving probes are monitored by more probes. Managing massive amounts of data from probe to probe is one challenge, but doing so flawlessly so tasks are performed perfectly each time, requires a well-trained and coordinated workforce of global experts who must use a common digital platform to share their data. For example, some of the parameters released by NASA to its contractor JPL and others for Curiosity’s landing on Mars included an entry speed of 13,000 miles per hour with an atmosphere one hundred times thinner than earth, a time frame of less than 7 minutes to touchdown and only a two-week window per year for launching from earth.

According to Ludwig, more and more projects will resemble the risk profile of Curiosity and the type of workforce needed to execute mission-critical projects. To that end Siemens currently spends over $500 million to train 1.2 million students per year. They also sponsor $100,000 rewards for innovation contests to encourage STEM (Science Technology Engineering Mathematics) career interest at both the high school and college levels.

Qualcom – Faster Access
Less on mission critical data and more on making room for more data through existing resources, Qualcom’s CTO, Matt Grob, focused on catapulting today’s 3G, 4G, and WiFi data capacities to 1,000 times faster access speeds by collating a clever topography of mini cell towers controlled by readily available  interference management technology. Overlapping signals from one tower to another would be automatically tweaked at just the right time to deliver an optimal throughput. The amounts of ‘Big Data’ to get the signals just right, are truly a task for machines. One can only imagine what new apps will emerge from an almost incomprehensibly faster mobile web connection, 1000x faster!

Iridium – Mission Critical Data and Faster Access
For ‘Big Data’ to be mission critical and responsive Matt Desch, CEO for Iridium, discussed his firm’s challenges with a global phone service that relies on an interconnected canopy of 66 orbiting satellites.  No matter where a call originates with an Iridium global phone, an Iridium satellite is no further than eight minutes away to pickup incoming signals and relay them to a central base station in Phoenix Arizona where calls are connected.

Iridium has reserved seven rocket launches from SpaceX to replace its aging fleet of satellites. The new fleet due by 2016 will unleash exciting apps including a top-down aircraft surveillance system that can save fuel by allowing planes to fly closer together and away from bad weather systems. At the end of his presentation, Desch held up a thumbnail-size ‘Iridium’ chip that enables any device to connect to its network including existing mobile phones. Perhaps, in the not too distant future, airline passengers will be able to make calls from their ‘Iridiumized’ mobile phones while in flight.

Xerox – Using ‘Big Data’ to Innovate
‘Big Data’ is not just about the collection of random data but also about the organic creation of more data.  The CTO at Xerox, Ms. Sophie Vandebroek, taps on ‘Big Data’ for innovation by treating its workforce as data points and deliberately mixing and matching unlikely pairs of experts to see what can happen. Xerox believes that innovation evolves when experts from different fields of study can look inward at a problem and lend a relevant suggestion. However, hitting a home run is analogous to winning a lottery ticket. For this reason, Xerox and other companies like Shell International with their “Game Changer” program encourage their participants to be critical from the out start and seek the fastest routes to failure before committing to a new idea.

In Summary
‘Big Data’ offers so many options for companies that without a clear set of objectives CEOs could run up huge losses from negative investment returns. Similar to chasing the end of a rainbow, ‘Big Data’ can become elusive, misleading, and overwhelming. One distinction that became clear from the EmTech 2012 conference was the growing importance of the Industrial Internet where machines communicate with other machines. Although the social data is useful for understanding markets and spotting new trends, industrial data is by far the platform-of-choice for what soon will become the ‘BIGGER DATA’.