Get Disruption Ready: Becoming Data Driven

Get Disruption Ready: Becoming Data Driven

“Go with your gut.”

It’s a term that governs management style in some circumstances, but the idea of going with how you ‘feel’ about something probably doesn’t apply to the major decisions you make about strategy, product, sales, and operations. If a decision ‘feels wrong’, it probably is, but the same may not be said of those decisions that ‘feel right.’ Many businesses don’t have empirical data on which to base major decisions. Whether it’s because it’s too hard to gather the data, or they’re heading into uncharted waters where, to coin a phrase “the customer won’t know what they want til they see it,” or because moving fast is better than being accurate, major decisions are made every day with little or no data to back them up. Changing your organisation’s mindset to one that demands data to backup major decisions can be a long journey, but there are a few benefits along the way.

Fast growing and disruptive market entrants have a few defining features. In our first post in this series, we talked about the five key corporate capabilities to focus your business on in order to be disruption ready. In other posts in this series, we’ve looked at building customer centricity – or putting the customer first – and enabling innovation. In this post, we cover something that underpins not only good decision-making, but many other corporate capabilities: how to become data-driven in your business.

The reason so many organisations fail to grow this capability is that knowing when, how and where to capture data on which to make decisions is hard. And it’s often made so by manual, siloed, or proprietary-software-trapped processes that your business relies on every day. If you want to make a data-informed decision on anything, you need to have considered, captured – or extracted – and analysed the data before you begin. You also need to have a curious mindset – one that seeks to know why things are how they are, and then wants answers that are justified by the numbers to back them up.

One great thing about the desire to know more and use data to back up that knowledge is that putting in place the right measures which continue to provide data as your business moves can point out and alert you to trends and changes that help you react, and even predict your next strategic move. On the other hand, wanting 100% accurate data before you decide on something can be nearly as crippling as having nothing on which to base your decision.

Here are some practical tips we suggest can work for you when becoming data-driven:

  1. Foster curiosity. It’s often the case that age-old processes, systems and structures have their roots in the ‘dawn of time’. When management teams are asked, there doesn’t seem to be anyone who knows why things are the way they are. But asking the question is powerful. The same can be said of assertions that don’t seem to have data to back them up. Worse, some assertions are made after looking at the data in a way that reinforces the theory of the onlooker. Known as confirmation bias, this can affect our ability to question or assess data for its true indicators, even when they don’t point where we expect. In meetings, or when reading reports, if the data doesn’t support the assertions, or isn’t sufficient to be able to make a conclusion, ask for more.
  2. Consider measurement from the start. When building or redesigning business processes and systems, or specifying platforms for your business, consider how you could measure whether the outcome has been effective. This usually means setting up measurement of the current state of play before rolling out anything new. You can’t ascertain whether a change has been effective if you’re not sure what the situation was before the change. Once you’ve worked out what you would need to measure, then you need to consider how to measure it – which is often the hardest part. If the ability to measure a system’s performance is a core criteria when considering a new system, then prospective systems which won’t allow easy measurement will tend to fall away and not make the cut.
  3. Visualise meaningful business measures. So many management reports are filled with data – graphs, tables, trend lines. But often these representations of data don’t add any value to the decision-making process because they don’t describe a meaningful measure. With the exception of core financial measures (revenue, profit, and so on), figure out what key indicators mean something to your business – new customer sign-ups? Inquiries? Closures? Or those which indicate the efficiency of your team, such as average business processes per day, team member or customer. Along with identifying the measures, if the measure is endemic to your industry, it can be useful to show these alongside benchmarks – average, median or other comparative numbers for your geography or vertical. Big swings away from the ‘norm’ could be an indicator of something major being awry in your business.
  4. Set up feedback loops. If a decision is based on insights gained from a measure that is based on data captured consistently and at the right time, continue to watch the indicator to see whether things return to the trend you were expecting or aiming for (or back towards leading industry benchmarks). For example, if it was costing you twice as much as the average company in your sector to acquire a customer, and you cut this cost through efficiency measures, keep watching the indicator over time and make sure the decision was the right one. And, watch for other indicators swinging about – profitability increases could be accompanied by decreased customer satisfaction indicators such as Net Promoter Scores – which could mean you’ve cut too much from the service end of the organisation.
  5. Be content with 80%. The quest to make decisions based on data can lead down a road of waiting for more and more data before a decision can be made. There’s a careful balance to strike between having enough data to be right 80% of the time, in order to move fast, and waiting for 100% accuracy and never moving at all. Don’t be the ones waiting for perfection, because it will never come. Best-guess based on a fair sized data pool is often enough to outrun the competition in a fast-moving industry. It’s about knowing when you have enough data to go on.

Becoming data-driven in your decision making doesn’t just apply to strategic or management decisions. Even comparatively small everyday decisions, such as improving a process or changing an advertising strategy should have some data as the basis for the change; before, during and after, so that decisions can be reversed, tuned, or accelerated depending on their effectiveness. The most important thing is that the quest for a data-driven decision-making culture drives how, when and where you collect that data, and how you analyse and gain insights from it to enable better decision making while not slowing you down.

Anthony Woodward is founder and Chief Executive Officer of Accelera