Around a decade ago, we first heard the expression ‘data is the new oil’. It was coined by Clive Humby, the man that built Clubcard, the world’s first supermarket loyalty scheme. He was using the metaphor to explain how data is a resource that is useless if left ‘unrefined’: only once it’s mined and analysed, does it create (potentially extraordinary) value.
When Humby presented his proposal for a loyalty scheme to the directors of Tesco in 1994, its chairman famously replied: “What scares me about this is that you know more about my customers after three months than I know after 30 years¹.” The launch of Clubcard doubled Tesco’s market share within a year to become the UK’s biggest supermarket chain. It was also, arguably, the world’s first example of what’s now known as big data².
The significance of data has only grown since then. We now live in a data-driven economy, in which the world’s five most highly valued companies – Alphabet, Facebook, Microsoft, Amazon and Apple – all deal in this precious resource³.
All companies have data, and all companies could stand to gain from it. The question is, are business leaders using their information in the best way possible?
Here are three sets of considerations to help drive maximum benefit from data resources:
If you were to ask a room of professionals if they have a LinkedIn profile, it’s fair to guess that the majority would have at least a mugshot and loose representation of their professional achievements published on the business networking platform.
In December 2016, Microsoft closed its acquisition of LinkedIn. Why is this relevant? In one of the most expensive technology deals in history4, Microsoft paid US$26.2 billion to purchase the business, which had 433 million active users globally. That’s the equivalent of about US$260 (AU$330) for your LinkedIn profile5.
Whilst you could argue LinkedIn has some impressive features (and probably more on the way) replicating aspects of its base product would not be beyond the capabilities of many developers.
In 2015, LinkedIn had revenue of US$3 billion (US$30 per active user) and net loss of US$166 million6. What the sale demonstrates is that LinkedIn is a data business: your data – not the LinkedIn product – is the currency that drove its extraordinary valuation.
Many businesses have an extraordinary amount of data, and there is huge potential for even small portions of it to be used to reduce costs or improve customer experience.
At the same time as pushing the boundaries of data to achieve business goals, however, it’s vital to understand customer expectations and, importantly, the limits of their comfort zone: what’s also known as the ‘freak line’.
If you’re a telco, for example, the ‘freak line’ might be crossed if you were to tailor advertising based on the content of your customers’ text messages. (As scary as this might sound, there are some platforms already doing this. Odds are, you have one of those apps installed on your phone.)
An example of where consumers might be more comfortable with sharing their data is a credit card company that mines its customers’ spending behaviour each month. It then recommends small businesses nearby where they might choose to shop. Of course, the credit card company stands to make money out of the scheme because shoppers will use the credit card to make purchases. But it’s likely the consumers won’t object to their data being leveraged in this way, because it translates to money being spent with small, local businesses.
It’s an interesting take on data being used in a customer-first approach. The credit card company has taken into account the relevance and context of how data is put to use, it’s thought about the customer’s needs, and then looked at the revenue opportunities that flow behind it.
All roads lead to respecting the permission that customers have given to use their data. Organisations need to build trust over a period of time; they must endeavour to show that they are respectful custodians of such information and, perhaps most importantly, that when used, it is relevant and in the context of the expectations that were originally set.
Data doesn’t always have a logical home, and data collected or managed inside one department is not always most valuable to that department.
Data sharing across business units may uncover huge benefits: experiments and hackathons (events that challenge a group of people to solve a particular problem in a condensed time period) can be great ways to explore the opportunities to leverage data in different ways.
Today, for example, we take parcel tracking for granted but it was FedEx in the 1990s that offered online tracking of deliveries as a free service7.
In businesses like FedEx, data was historically used for internal planning such as workforce and fleet management. The individual tracking numbers for parcels were originally employed for quality control. However, the opportunity to share that same tracking information directly with the customer enabled FedEx to transform its customer experience and arguably pave the way for the e-commerce landscape of today. (The founder of FedEx, Fred Smith, said: “The information about the package is as important as the package itself.8”)
Seeking to uncover data-driven insights in your organisation? Visit the ‘Unlock data possibilities’ website.
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