Recent research on Big Data should sound an alarm bell for companies. On the one hand, there is a link between usage of Big Data and the quality of corporate performance, on the other, very few companies are actually making use of Big Data. Companies therefore need to grasp the commercial advantages that Big Data can bring, and determine how they can develop their capabilities and culture to exploit its potential.
Writing in the Harvard Business Review in 2012, Andrew McAfee and Erik Brynjolfsson revealed the extent of Big Data’s impact. They interviewed executives in 330 publicly traded companies in the United States and found that those organizations which believed most in the power of Big Data gained a marked advantage over their rivals. According to McAfee and Brynjolfsson, the enterprises that were in the top third of their industry in terms of using data-driven decision making were more productive and more profitable than competitor companies by average margins of 5 percent and 6 percent respectively.
Despite such findings, companies have not broadly adopted Big Data practices. Indeed, a 2013 Gartner survey found that less than 8 percent of surveyed companies had actually deployed Big Data technology. Although this figure is set to rise substantially in coming years, companies will need to adapt considerably to thrive in a data-centric world. In the Aberdeen Group’s “Big Data Trends in 2013,” the authors found that the proportion of executives who reported that their companies were unable to use unstructured data, and who complained that the volume of data was growing too rapidly, had increased by 25 percent during the previous year.
Stages of maturity
So while better technology will help to store and analyze the avalanche of data now being produced, what will make the difference is building the right capabilities and culture. To do this, companies will need to know where they stand in terms of a Big Maturity Framework. The framework consists of three elements — environment readiness, organization-internal capabilities and the ways in which Big Data can be used. It can help companies to see how far they have progressed, and identify what more needs to be done to get where they want to be.
In its most developed phase, it can radically reshape the business landscape
The framework acknowledges that Big Data can be used in different, progressively more sophisticated, stages of maturity. It can have a limited scope, serving merely to improve the efficiency of existing operations. Or in its most developed phase, it can radically reshape the business landscape, transforming individual companies, and paving the way for disruptive, entrepreneurial start-ups and the creation of wholly new industries.
The first maturity stage, performance management, allows executives to view their own business more clearly through, for example, user-friendly management information dashboards. This would typically involve internally generated data.
The second maturity stage, functional area excellence, involves organizations using both internal and external data to improve selected areas of the business. This may lead to the enhancement of sales and marketing techniques, or to advancements in operational efficiency. For example, one German car manufacturer used real-time performance monitoring of production machinery to achieve a 20 percent increase in productivity. Each machine was closely monitored to pinpoint downtime, enabling the company to optimize the utilization of the overall plant.
The third maturity stage, value proposition enhancement, allows organizations to start to extract a new source of competitive advantage that goes beyond the incremental improvement of existing operations and services. This may entail real-time recommendations, or the personalization of services, to raise the quality of the customer experience.
For example, a global mass merchant was able to increase its profit per customer by 37 percent by applying advanced customer analytics to identify its best customers and then present them with personalized offers. The frequency of those target customers’ purchases rose by approximately a quarter, and the average basket size grew by around 10 percent.
Another example of this third maturity stage comes from a leading European bank. This financial institution managed to increase sales by 12 percent through diversifying its website content. When customers logged in, they were shown one of several alternative websites based on their individual transaction history and segment, and the company’s overall product portfolio. The content was adjusted according to the predicted needs of the customer in order to maximize potential sales.
The fourth and final stage, business model transformation, is when Big Data leads to fundamental change. Big Data practices become deeply entrenched within the organization, shaping the nature of the business as well as the mode of executive decision-making.
Both product and services organizations are capable of reaching this stage. General Electric (GE) is a product organization that has made clear that it believes in the power of Big Data. The company anticipates that machinery and equipment will soon be loaded with sensors which will display detailed service data in real time and across longer time periods. GE is therefore spending more than $1 billion on building up its data science capabilities to provide data and analytics services across business functions and regions.
The proposed merger in 2013 of the two advertising companies, Omnicom and Publicis, indicated a broader data-driven transformation among service providers. The advertising industry is moving toward a more science-based, data-driven business that aims to deliver personalized advertising messages. This new world will be dominated by those major players that possess the most comprehensive data about individuals. Although they called off the merger in May 2014, Omnicom and Publicis believed that their combined size would produce the desired volume of data.
Yet despite widespread interest in Big Data, companies face many pitfalls. Many of these relate to their own internal systems and culture.
One prominent obstacle is the shortage of available data-scientists with an advanced education in mathematics or statistics who can also translate raw material into actionable, commercial insights. Although many educational institutions have started to introduce relevant courses, the market demand for such people is already considerable.
Companies must also refashion their current decision making culture. Senior executives should be making more judgements based on clear data insights, rather than simply resorting to their intuition as in the past. Changing corporate culture in this way could well impinge on concerns relating to status, with executive instinct increasingly challenged by the facts of hard data.
Over the next five years, Big Data will become the norm and will enable game-changing opportunities in many industries
However, while data can be of great assistance in solving an actual problem, it nonetheless holds true that senior management has first of all to ask the questions that the data at their disposal could usefully answer, rather than process it with no clear strategic goal in mind. What this means is that the value of an insightful executive will not be diminished in this new era, but rather can be enhanced thanks to Big Data.
Over the next five years, Big Data will become the norm and will enable game-changing opportunities in many industries. Organizations must react in a timely manner to determine how they can deploy Big Data in the most effective way possible, and then lay the appropriate groundwork. Without the necessary senior-level enthusiasm and sponsorship to realize the huge potential of Big Data, savvier competitors are likely to gain a potentially decisive advantage.
Correction: A previous version of this article, which appeared in Executive’s print edition on May 1, mistakenly claimed that Omnicom and Publicis had actually merged.