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The Mission Log

If data is such a valuable resource why are people struggling to get value from it?

“Data is the new oil” A much used (and abused) quote, that underlines both the transition from a manufacturing based economy to a digital economy and the key resources that drive both.

But trying to exploit data in the same way we exploit oil is not a viable route to success.  Unlike oil, data is a renewable resource that gains in value the more people use it. This article explores the new skills, strategies and ways of thinking that leaders need to understand if they want to thrive in an increasingly data-driven world.

Clive Humby (the co-founder of Dunnhumby the consumer data business) is credited with coining the phrase “Data is the new oil” and could rightly claim to know what he’s talking about given that he co-created a data-driven company that’s now worth an estimated $2billion.  And, yes, data is clearly a valuable asset.  As well as helping retail giants better understand consumers, data now drives new insights and services across every sector from finance to healthcare, from farming to gaming.

“So far so obvious” you might be saying.  And I’d agree.  But here’s the thing.  Whilst most leaders see the value in data, how many can confidently claim to be using data to drive real value for their business?  There’s no shame in this.  Like any systemic shift, there’s a significant lag between spotting a new trend, finding new opportunities in what’s changing and being able to exploit the change.  Consider how long it’s taken businesses and government to adapt to the web and how many casualties there were on the way.  Even the smartest people can miss what’s going.  Kodak’s leadership team weren’t stupid.  But they nonetheless completely missed how digital was changing the photography sector, leading to the once world leader’s famous bankruptcy.

Kodak camera (photo credit – Wikipedia)

How did a business that in 1976 commanded 85% of camera sales in the US miss what was going on?  The story features in many business school case-study classes.  But I’ll save you the time and expense of an MBA course by telling you that at its core it’s about not adapting to new ways of thinking and doing business.  Applying old strategies to new situations.   Not seeing the wood for the trees.  And this is why, if you’re a business leader, thinking about data as oil is dangerous.

Oil was a resource that is exploited using industrial age strategies and economics.  Data is very different.  For data to be effectively exploited leaders need to undertake a shift in the way they think about resources.  This shift is as different as digital photo sharing is from a handing round a polaroid picture.  And understanding why things are so different is a great place to start a data-driven journey.

Data gets more valuable the more people use it

Unlike oil, data can be owned and used by many people, simultaneously. Often, the more people use data the more value can be derived from it.   So whilst a proven strategy for making money from oil is to tightly control supply and sale, doing the same for data may well reduce its value.   Which is why leading businesses like Thomson Reuters and Syngenta publish data openly – so that anyone can access, use and share it, for any purpose.  Thomson Reuters make money by using open data to draw clients into their services.  Syngenta makes money by providing evidence for how they claim to create a positive impact on farming – reducing inputs like water, whilst increasing outputs.  Both businesses also use this data as a way of engaging a broad range of people, including customers, suppliers, journalists and regulators.  Direct benefits abound, but what can be even more exciting are the unexpected opportunities that arise when a company uses openly shared data to place itself at the heart of its eco-system.  One direct example of this is when data-consumers discover mistakes in data and alert the publisher, as happened when a British schoolboy found mistakes in NASA’s data from the ISS.

Data skills are different

The skills need to work with data represent the next stage in the knowledge-based skills evolution that started with the web. Data requires different strategies and business models. Similarly, delivering effective data projects often requires adopting newer techniques like Agile – allowing value to be created incrementally in weeks rather than years, and enabling a project to adapt and learn, based on feedback and changing circumstances.  The key questions leaders need to ask are “Do I have the data literacy required to make the right decisions and craft a data-driven strategy?” and “What data skills does my business need?”.

Find out about the ways leaders should think about their skills in this article – 3 steps to becoming a data-literate leader 

Open and shared business models

Some of the most innovative and valuable data-driven businesses put shared and open data at their heart. This allows them to both control and develop a data-infrastructure that allows them to get where they want to go. A good example of this is Uber.  Uber doesn’t own much of a physical infrastructure – they’ve developed the data infrastructure that allows them to quickly connect people to cabs.  They share data on the ratings of both riders and drivers which improves trust and usage of their service.  They exploit data to develop new products, increase efficiency and improve their service. At the other end of the scale openly releasing data has been an effective way for retail data business Geolytix to be found, to draw in potential clients and to establish themselves at the heart of their eco-system.

Starting Small is the Way to Start

Like the web, the data-revolution is going to be a tricky one for leaders to navigate. Businesses still tend to fall back to oil-age thinking – jealously guarding data, crafting systems and strategies to sell it.  But doing this will mean missing key trends and new opportunities. Sometimes it’s inertia that stops people getting started.  And this can be made worse if leaders attempt the wholesale transformation of their organisation – never an easy thing to do, and probably impossible when the data revolution is moving so fast.  Which is why it’s best to start small, finding discreet projects that can create value in weeks and months rather than years. Learning the lessons from smaller projects will provide pointers to longer-term changes and identify opportunities that deserve the kind of large-scale support that will drive deeper organisational changes.