Without data, you are doomed to fail

While there is a lot of talk about big data and analytics, few organisations have actually mastered the use of data to advance their business. What does it mean to be truly data-driven and how do you get there? We asked Öykü Isik, Professor of Information Systems Management.

“A data-driven enterprise uses data and data analysis on a daily basis to inform decision-making and business strategy,” explains Öykü. “It sees data, or rather the insights gained, as a means to differentiate itself from the competition by providing a better customer experience and service.”

The technology is ready and so is the customer

The use of data and data analytics in business is not entirely new. Thomas H. Davenport already started writing on data analytics in 2005, before publishing his bestseller “Competing on Analytics” in 2007. And well before then Netflix and Amazon had already built powerful recommendation engines that enabled them to predict customer interests and offer personalised suggestions based on previous purchases.

“They were pioneers more than 15 years ago and they’re still leaders, even though nowadays every website features review and comment options,” says Öykü. “What has changed since is the available technology to make sense of massive amounts of structured and unstructured data. That has improved exponentially. We now have the tools to convert data into insights that help improve the customer experience,” she explains, adding: “But it’s not only the technology that has driven recent developments, customers have come to expect personalised recommendations and other service improvements made possible by the use of data and data analysis.”

More than marketing

Business intelligence, big data and data analytics projects are often launched at the initiative of the marketing and/or sales departments. But the opportunities of careful collection and analysis of data go well beyond these functions. Decision-making in general, marketing and sales growth, operational and financial improvement, risk and compliance management, product or service innovation, the possibilities are endless. Öykü recalls one project in particular: “It was an impressive analytics project at a bank, set up to automate parts of the audit process in order to make it more efficient.”

Four pillars

How do data-driven organisations differ from others? What are typical success factors? They have the technology, but also the people and the mindset. In “Competing on Analytics”, Davenport identified the four pillars of analytical competitors:

1. Data analytics is used to support a strategic distinctive capability, only then will data and data analytics support strategic, long term growth.

2. There is strong senior management commitment because competing on analytics requires changes in corporate culture, processes, behaviour and skills of almost everyone in the organisation.

3. There is an enterprise-level approach rather than one department or a haphazard selection of individuals across the organisation being involved in data analytics. Data and tools are made available throughout the organisation.

4. They have a large-scale ambition as they bet their future success on analytics-based strategies.

Other success factors

“Davenport identified his four pillars in 2007, but I’d like to add some more,” Öykü says. “In data-driven organisations, big data and data analytics are no longer the realm of the IT department, they’re embedded in the entire organisation. For years we’ve been talking about business-IT alignment, but the reality is that in most organisations, IT still has a support function. Now, more than ever, it should be a partner, with a seat on the board, working with the business in tandem.”

“Data-driven organisations are also agile,” she continues. “For many organisations this means they will have to change their project management style. So it’s out with the waterfall model, in with agile, iterative development and short release cycles with plenty of user involvement. Which brings me to experimentation. Data-driven organisations have a culture of experimentation. They encourage data experiments to gain new insights and to identify new opportunities.”

And then there is customer empathy. “The importance of empathy has long been ignored. But humans react to emotional probes, rather than objective product features. Successful data-driven enterprises, using data to improve their customer-facing processes, understand the importance of customer empathy and have embraced service design thinking, which puts empathy at the heart of the service creation process.”

Design for privacy

What about the elephant in the room? If we talk about data, we should talk about data privacy and privacy management. Data-driven organisations must strike a balance between the need to gather data and the need for customers to trust the organisation, as Öykü explains: “Transparency will pay off. Companies that are transparent about the data they collect, why they collect it and how it is used will come up trumps. If customers can see the benefits of sharing their data, for example more personalised services, and they trust the organisation, then privacy is no longer an issue.” She stresses that companies do well to think about privacy-sensitivity right from the start. “Privacy management should be a standard feature of any data analytics initiative.”

The tools exist to offer customers personalised recommendations, but no matter how transparent the organisation is about its privacy policy, some customer are simply not willing to share data. For Öykü this need not be an issue: “Customers are typically segmented along demographic dimensions, but privacy sensitivity could well become another dimension. Less privacy-sensitive customers could receive more personalised offers, for example.”

Not without a plan

So, you want to become a data-driven enterprise. How do you go about it? “Your ambition should be large-scale, so think big, but go about it in an incremental fashion,” she says. “First, spot opportunities for data collection and data usage, then identify a good pilot project to build the business case, i.e. to prove the value and to convince people. Good pilot projects have a high visibility and a short turn-around time. It’s a pretty standard approach, really.”

One warning though: “Take it one step at a time, but not without a plan. Make sure you know where you are, where you want to go and how to get there.  Determine KPIs to evaluate and monitor success and to ensure execution is aligned with strategy.”

The transformation into a data-driven organisation is a huge change project. “Data ownership is a particularly sensitive and political issue. So be prepared for the usual power games – they’re bound to surface,” she says smilingly.

Today’s opportunity, tomorrow’s constraint

Now is the time to act. “If you think you can postpone any plans to become data-driven, you’ll be disappointed. However, you’d be forgiven for being a bit sceptic. The ERP systems seemed a huge opportunity back in the 1990s. But nowadays, these monolithic, closed systems have become constraints, hindering organisational agility.” Nevertheless, Öykü believes this is a bad excuse to sit on the fence. “The window of opportunity is here and now. Companies that fail to make good use of data are doomed to fail.”

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