Wilson Fletcher

Imitation versus innovation: the data trap

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More and more, organisations who rely on data for their direction will look at their competitors and see a reflection of themselves.

Data is undoubtedly seen as one of the greatest business assets of modern times: a great partner in a world of frantic pace and continuous change. If collected and analysed correctly, data can help organisations make continuous improvements to their live services by tracking the performance of key characteristics in real-time and addressing them with appropriate changes.

Whether it’s the prominence of a story based on pageviews per minute or the promotion of one product against another, data is powering thousands of small decisions each day in services across the world.

In this context, data gives us consumers more of what we want (in the examples above, articles we like to read or products we like to buy) and by doing so it gives service owners more of what they want (ad impressions, engagement, sales revenue). It’s apparently a big win-win and data is doing the heavy lifting in the relationship.

However, there’s a sting in the tail for the people at both ends of data-powered services: convergence. It’s why in any mature sector, digital services become more and more alike over time. This convergence is driven by a simple confluence of factors in which data plays a central role.

The pattern always goes something like this: in any given sector, where market dynamics are alike, data will give similar clues to competing service owners about active consumer behaviour. They will then adapt their services accordingly, in an increasingly common direction. Consumers, served by increasingly common services, will exhibit increasingly consistent behaviour, making choices between services based on smaller and smaller degrees of difference.

A spiralling pattern of convergence is an almost inevitable consequence of using data to drive service development. Services converge in their behaviour due to increasingly aligning data points and consumer behaviour converges as people are ‘taught’ how to behave by the consistent experiences in that category. It’s the ultimate chicken and egg and it’s happening in almost every established sector worldwide, from booking flights to buying clothes.

The result? It becomes increasingly difficult to maintain any degree of competitive differentiation and loyalty. Consumers can more easily move between competing services. Competition increasingly occurs at a fine-grained functional level.

Part of the problem is the inherent nature of data and analytics. By their nature, data platforms record and report against current behaviour. Some of the fancier systems will plot likely trends and machine intelligence will improve that predictive capability. Data’s perceived infallibility is down to its point-blank refusal to show you what it hasn’t seen.

Data is a powerful source of operational intelligence because it’s a highly accurate representation of what has happened up to and including this instant. Decisions can be made confidently because they’re founded on real-world operational data.

Unfortunately, over the road a similar data platform is feeding your competitor a similar set of operational data, and over the road from them another platform is doing the same to the next company in the sector. Each company is acting on hard, empirical data to confidently improve its service – and is unconsciously making it a little more like its peers with each ‘improvement’ made.

Of course, time is a factor: those who act fastest can achieve at least temporary competitive advantage if they respond to what their data is telling them quickly. Design is a factor too – how they respond makes a big difference to how well they can capitalise on their data intelligence. A redesigned widget, process, or screen can bring immediate competitive advantage if it’s better than competitor responses.

In both cases, a smart, intelligent response will gain some advantage. But in both cases these advantages are usually extremely short-lived. As soon as the changes go live to customers, competitors can copy them (without the cost of coming up with them), making the differences small again.

And so the cycle repeats. No matter how you try to progress, if you rely on data your relative differences will continuously and progressively shrink as you converge with your competitors. Convergence, ironically, is the price of improved data intelligence.

What can you do about it? Firstly, keep collecting and using operational data. Don’t stop using data to power incremental changes and adaptations to your service.

But do stop relying on data to inform your future direction. Remember, it’s great for telling you ‘what’, but terrible for telling you ‘why’. And it’s completely blind to a ‘what if’, ‘what else’ or ‘what instead’. To fix the convergence problem you need to broaden your horizons to generate counterpoints to your operational data.

Design research techniques can uncover incredibly powerful insights that really make you stop and think. Equally, getting a new perspective on your broader service strategy can identify new areas of opportunity to take advantage of. Both can help challenge assumptions and force an objective evaluation of the return on investment from those incremental changes.

Convergence is accelerating and in many sectors material competitive differences are almost indiscernible. More and more, organisations who rely on data for their direction will look at their competitors and see a reflection of themselves.

So watch out. Data appears to be a supportive and attentive partner: always on your side, always watching out for you…while it’s sleeping with all of your enemies.

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Stop relying on data to inform your future direction. Remember, it’s great for telling you ‘what’, but terrible for telling you ‘why’. And it’s completely blind to a ‘what if’, ‘what else’ or ‘what instead’.