Big Data is big news. Not a day goes by without some article proclaiming how Big Data will solve long standing social and economic problems, in areas of education, healthcare, public policy, workforce efficiency, supply chains, and so on. The question, however, is how companies actually transform Big Data into growth and value-added information.

And make no mistake – Big Data is big business. IDC predicts the Big Data and Analytics market will grow 50%, from €40 Billion in 2015 to €60 Billion by 2019. Companies clearly see the potential to extract meaningful intelligence from Big Data. With innumerable sources of data, if we can only analyze it effectively, we will usher in a new dawn of actionable insights that will drive transformation, innovation, and profits.

So why have we not yet seen the Big Data revolution? Where are all the Big Insights we have been waiting for?

The problem isn’t the amount of data. In fact, we estimate that the amount of data is doubling every two years and will reach 44 trillion gigabytes by 2020. Yet this same study estimated that “less than 5% of the useful data was actually analyzed.”

So we are awash in data sets but are only utilizing a tiny fraction. Why is that?

Imagine the Marketing department wants to explore whether certain attitudinal measures drive tangible benefits to the business. Easy enough. Survey your customers and correlate the survey data with database metrics, such as number of visits, average wallet size, and so on. However, there will inevitability be numerous data issues to consider on the back end. Should we remove outliers from the survey? Does an atypical distribution of survey responses indicate an anomaly to be treated with suspicion or an important sub-segment of the market that we discovered? Our database metrics will pose an even greater challenge, as some customers will have data on certain variables and not others. Do we restrict our analyses to only customers with the full set of database metrics? If not, how do we treat missing data? What about the even greater challenge of integrating third party information?

Even in this fairly straightforward example, there are many decisions to be made. The process of cleaning and preparing the data for analysis would likely take many weeks. The challenges are exponentially greater with Big Data, as the data points are novel, numerous, diverse and – perhaps most importantly – in different formats.


While the promise of Big Data is sexy and prone to attention grabbing headlines, the sober truth is that most Big Data work is boring and tedious. On the other hand Big Data is creating huge opportunities but many companies aren’t taking advantage. What is your company doing?

The number one topic for CEOs for the past two years has been Big Data. According to the Conference Board’s CEO Challenge survey, CEOs see that the exponential growth and availability of data — the Big Data revolution — is transforming the business environment and creating huge opportunities for their companies. Nevertheless, research shows that most traditional companies are still not leveraging Big Data to create better business models for themselves.

MEDIQ, a major Dutch health care company, is a very good example of a company that has successfully harnessed Big Data to transform its business model. In 2012, the Dutch government deregulated pharmaceutical fees, triggering an immediate 90 percent drop in the company’s profits. MEDIQ had no choice but to rethink its business model. Under the leadership of a new CEO, the top management team boosted a company shift: from seeing its main mission as the packaging and distribution of medicines and medical supplies, the company switched to looking after patients. MEDIQ transmuted its DNA. Big Data made this change possible.

An external company was brought in to estimate – using Big Data – yearly hospital admissions per patient and the total cost to insurance companies. By knowing their customers and tracking their history of medical treatment, MEDIQ could avoid many admissions. The company then proposed to share the savings with the insurers. The resulting deal accounts for around half of MEDIQ’s total current profits.

By using Big Data to get to know its patients (80 percent of prescriptions are refills for chronic illnesses and 99 percent of the customers always buy at the same pharmacy), MEDIQ could foresee 80 percent of demand more than one month in advance. General forecasting became practically unnecessary and it only had to focus on predicting the remaining 20 percent of demand. As a result, MEDIQ’s distribution model also changed. With advanced knowledge of demand, the company could reduce its overall inventories by 50 percent.

When MEDIQ decided to embrace Big Data to make its survival shift, the whole company changed – its business model, its mission, its services and the way it made its money.


To take advantage of the opportunities offered by Big Data, companies need to adopt strategies that will fall between any of these three instances:

1] Digital fit: A company can pursue digital “fits” to exploit the advantages of Big Data and seize the opportunities for improvement it offers.

Thanks to the implementation of a system to visualize delivery routes, some organizations are saving 15 to 20 percent of their total transportation costs.

Digital fits may turn out to be as important for companies as was the introduction of the computer. Back when computers were new on the scene, it was thought that they would change processes but not lead to fundamental shifts in the way organizations operate. Today we can’t imagine a company working without them.

2] Digital masterplan: Where a company faces a fight for survival and needs to review and change its overall strategy, it will require a digital master plan.

Fast moving consumer goods sectors, such as toy manufacturers, are witnessing the rise of a new consumer profile that combines the digital and the physical worlds (playing digital games and online shopping, for example). To respond, a company needs a master plan for the digitization of its business.

3] Digital DNA: When a company’s DNA becomes digital, it goes through a transmutation: it changes its whole business model. The company’s strategy, therefore, has to shift toward one driven by big data. Some organizations are already including big data in the core of their business.

However, incorporating Big Data may not be as straightforward as it seems. If we look at the toy industry, the sector is certainly experiencing a situation that could go in many directions. All industry players seem to agree that the digital fusion implies a change that is here to stay. But to what extent will this justify a shift in the whole strategy of a company?

A toy company may choose to become digital down to the core of its business and adapt all its toys and games to a digital ecosystem. Or it may choose to just create a strong digital strategy, keeping the essence of the company (and its toys) untouched.

To navigate this Big Data tsunami, executives need appropriate business tools. They need to “unlearn” past models that were based on stable industries and embrace tools that are based on managing ecosystems.