Technology & Innovation

Big data and consumer products companies

March 18, 2013

Global

March 18, 2013

Global
Trevor McFarlane

Senior editor

Trevor McFarlane is a senior editor for the CEMEA region at the EIU. He is responsible for covering a range of industries with a special focus on the Middle East. Prior to joining The Economist Group in Dubai, Trevor lived and worked in Istanbul, Doha, Riyadh and Abu Dhabi. He grew up in Ireland and is a graduate of Dublin’s Smurfit Business School.

Big data and consumer products companies: People, processes and culture barriers is an Economist Intelligence Unit report sponsored by SAP.

Report Summary

Big data and consumer products companies: People, processes and culture barriers is an Economist Intelligence Unit report explores a range of issues associated with successfully implementing so-called “big data” initiatives within the global consumer products sector. In particular, it focuses on people and skills challenges; process and organisational structure considerations; and cultural changes as a result of such initiatives. The research was sponsored by SAP.

The likes of Google, Amazon and Facebook tend to capture the majority of the headlines relating to running data-based businesses. Yet a quiet revolution is under way within the global consumer products industry. Unilever alone claims that 2bn people use one of its products every single day, while Proctor & Gamble (P&G) handles over 4bn daily transactions. Indeed, although much of the technology industry is often prone to hyperbole, the consumer products sector truly has the capability to generate “big” data—spanning point-of-sale information, customer sentiment, weather forecasts, supplychain tracking and far more. But working out how best to fully exploit all these data for competitive advantage is another challenge altogether. Many focus on the technology issues alone, which is certainly one key consideration, but is not the biggest difficulty in big data. Instead, there are several other major challenges, often overlooked, which this report seeks to highlight. Some of its findings include the following.

People, processes and culture, rather than technology, are the biggest challenges to overcome in fully implementing big data within consumer products companies. While the headline technology figures and challenges are often startling—as early as 1998 P&G had already captured over 920,000 gigabytes of data, for example, which is no mean IT challenge—many experts and executives agree that the technology issues are not the biggest barrier. Instead, the real difficulties lie elsewhere: finding the right people and skills to make use of such information; adjusting organisational processes to take advantage of the insights generated; and switching the management culture to one that is far more data-centric in the way it operates and makes decisions.

A severe skills shortage is the most obvious barrier to growth, with consumer products firms competing for scarce talent across deep-pocketed rivals. Probably the single most pressing issue for consumer products firms seeking to tap big data is a shortage of talent. Until the job title was coined in 2008, the role of “data scientist” simply didn’t exist; today, just one online jobs site in the United States lists over 8,000 such roles, while another in the UK lists well over 1,000. The Harvard Business Review recently dubbed it the “sexiest job of the 21st century”. But with demand far outstripping supply, these roles will not all be filled. And for the consumer products sector, the challenge of hiring is exacerbated by the fact that they are competing for this rare talent against the likes of hi-tech firms, banks and biotech companies, all of which are willing to pay generously to secure the people they need.

As consumer products firms seek to uncover new insights from big data, they will need to give thought to the organisational
structures and processes needed to properly take action on these.
To make the most of what a datacentric business can offer, consumer products firms will need to change how they act on the insights generated. While existing analytics queries are often more vertically focused (for example, how are customers reacting to this specific product), big data can often garner more horizontal insights across the business (which products are likely to do better or worse this year, perhaps). This raises questions about where a specialist data team is best placed within the organisation—to whom should they report, and what degree of autonomy should they have to suggest radical new approaches, among other considerations.

The era of big data will raise new questions about where this core competency is placed within the business. Just as many companies debate the merits of centralised versus decentralised in functions such as finance, marketing and IT, so too is this a consideration within big data. Data initiatives are often launched within specific product lines or to support a particular customer initiative, but many believe that this will increasingly become a more centralised function, reporting to a key C-suite role such as the CFO or even the CEO. And even if this does not transpire, others see a chance for the era of big data to make IT a more strategic partner for the rest of the business. Regardless of how this debate plays out, IT has a clear role to play in making big data-related queries simpler, more visual and more interactive for managers and analysts.

 As instinct gives way to evidence, management cultures within consumer products firms will need to adapt. Several management adjustments lie ahead for consumer products firms adopting big data. Given the expanding variety of data now being gathered—from point-of-sale data and consumers’ social media posts through to customer location information—leaders are having to get far more creative in the kinds of questions they ask. In parallel with this, executives are finding that decision-making is happening much faster, and often within a more collaborative, crossfunctional environment. Others are reconsidering how accurate data need to be before they become useful and actionable. All of these shifts imply changes in the nature of the decision-making and leadership culture within the consumer products business.

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