Big Data is The Answer — But what is The Question?
Answer this simple question to see if you are ready for Big Data
Companies big and small are investing billions in Big Data capabilities. However, many still struggle with the basics of using data analytics to guide business decisions. The reason for this is not technology, but culture. Before embarking on a major Big Data initiatives, managers should ensure that their organisations have a genuinely effective culture for data-driven decision making.
Big Data is Here!
Big Data is everywhere. Seemingly every business problem can be solved by sifting through mountains of data and distilling it into revolutionary insights about customers, competitors, and profit drivers. At least this seems to be the case if vendors of exotically named data processing, analytics and visualisation software are to be believed.
Trust in the force of analytics is strong. Big Data vendor revenues have grown explosively and are expected to continue to grow over 8% p.a., reaching $85bn by 2026. In contrast, the global IT market is expected to grow at only 2.5% p.a. over the next few years (Gartner, 2016).
All this investment comes with big expectations. According to McKinsey, Big Data will be the “next frontier for innovation, competition, and productivity”. Business strategy may soon be designed by algorithms (Sloan Management Review), and information processing systems could learn to understand humans better than we do ourselves (Financial Times).
So then, all a company needs to do is to invest in some cloud computing capacity and hire a bunch of data scientists to transform into a “data-driven company”?
Well, not quite.
Big Data is Hard
In reality many companies — even large multinationals — still struggle with the basics of data-driven strategic decision making. Thus, some run the risk of investing in advanced analytics solutions that they are simply not ready for. Recent research shows that a significant proportion of organisations have difficulties gaining competitive advantage from analytics.
Are You Ready for Big Data?
To test your readiness for Big Data, see if you can answer “yes” to this one simple question:
Do you really know your customers?
Who are they? I am constantly amazed by how many companies still struggle to answer the very basic questions about their business: who are our customers, what are their needs, and which ones make us money? The answer does not need to be a meditation on the essence of a customer. Being able to reliably state how many customers one has at any given point in time would be a great start.
When the new CEO of a financial services business was looking to find out how many customers the company had she found the answer to be between 80,000 and 120,000, depending on who she asked. Finance defined a customer as someone who had made a transaction within the last 12 months, Marketing thought everyone who has ever signed up is a customer, regardless of whether they had ever used the service. Operations had yet another definition. As a result, nobody really knew…
What are their needs? Knowing how many customers one has is a good start, but of course not enough. Sensible businesses should seek to understand what their customers need and are happy to pay for. Typically, this requires needs-based customer segmentation. However, despite of several decades’ worth of marketing literature teaching us otherwise, crude demographic or product based segmentation is still pervasive. For example, if you are renting a car for several days, the chances are that you are labelled a “multi-day” customer, regardless of who you are and what your real needs might be.
Who makes us money? An engineering services provider with growth and profitability problems changed strategy to target multi-year contracts with large, global customers instead of serving smaller customers’ ad hoc requests. The company won several contracts, which were celebrated as great victories. However, profitability problems persisted. A consultant brought in quickly found that while the large contracts generated revenue growth, they also required a lot of support activities that created significant costs. None of these “indirect” costs were included in contract pricing. As a result, the engineering company was at best breaking even on the celebrated contracts
Similar stories are familiar in many companies. Lack of reliable data on the basics of a business creates a number of practical problems. Customer KPIs are skewed. Analyses on the effectiveness of customer acquisition and retention spend can be heavily distorted. Risk and compliance management becomes challenging. Management discussions may descend into arguments about the validity of data, rather than solving the matter at hand. Further, failure to answer such basic questions may also signal fundamental issues with a company’s management culture and capabilities.
It’s All about Culture
Technology may be seen as the cause for the inability of companies to effectively use analytics. Data may be disjointed — different systems capture business-critical information, such as pricing and cost data, in inconsistent and incompatible formats. Lack of format preservation encryption may make the use of data stored over time cumbersome, or impossible. And even if technology is aligned, data definitions often are not — resulting in lack of shared, unequivocal understanding of what KPIs really mean.
However, it’s not about technology or accounting definitions, it is about culture. Data-driven culture is about asking the right questions, and expecting data driven answers. Culture is about consistent, shared definitions of data and KPIs. Culture is not about blindly trusting analysis or mechanistic decision making, it is about enabling productive debate and decision making on strategic issues.
Over time, many companies undoubtedly will benefit from Big Data. However, without a genuine data-driven culture, Big Data may become just another search for an easy fix to hard problems.
Before embarking on a costly and complicated analytics project, my advice is to go back to basics and make sure that your company has a solid understanding of its customers, markets and performance drivers, even if this analysis is based on “small data”.
The author is an experienced strategy director. This article is written in personal capacity.
