Five ways to become a data-driven organisation

Five ways to become a data-driven organisation

Ben Nadel
by Ben Nadel

Becoming data-driven has been a widely advertised objective for many organisations these last few years. While investment in the aim has increased, progress has been slow. According to a 2019 report, 92% of firms are increasing the pace of their Big Data and AI investments, but only 31% identify as data-driven. Three years ago it was 37%, so it would appear that data-driven behaviour is in decline, despite the rising investment. This suggests that technological investments aren’t reaping the desired rewards, so what is the answer?

Being data-driven means making decisions with hard data, not your gut. To demonstrate how hard this actually is The Economist’s Intelligence Unit spoke to 174 business executives (51% c-suite) and found that when the data contradicted their gut feeling, only 10% would take the course of action suggested by the data. This indicates quite strongly that the issue appears to be cultural and behavioural, rather than technological.

In light of these alarming statistics, what cultural and behavioural changes can organisations make to become more data-driven?

1 – Serve the data where it is needed

All too rarely does someone decide to run a data request to inform a decision. Whether it is a fear that the data will not support their gut, difficulty getting the data, or simply the awareness that relevant data exists, big decisions are often made in the absence of data.

Organisations that proactively serve data to decision makers stand a better chance of making data-driven decisions. This starts with an assessment of what data would be most useful to an individual and when best to serve it. Invest time in determining the most valuable data for someone’s role and working with them on how and when to serve it.

This goes far beyond the traditional, cyclical Management Information (MI) that gets distributed to stakeholders on a regular cadence. It should be about ensuring the right data is available in the right format, on demand for decision makers.

2 – Embrace and address bias

Whether consciously or not, data will often be used to support a preconceived belief, rather than viewed entirely objectively. To make better, more informed decisions from the outputs of analysis, this confirmation bias needs to be appreciated, fully understood and consciously addressed.

By investing the time in fact-based conversations to unearth bias that has gone unnoticed, or reviewing the data to ensure it is correct, the business can use this greater understanding of what the data is really telling them to make changes that might otherwise have been overlooked.

3 – Collect data to answer better questions

Banks have extensive data stores, but they are almost never exhaustive. In the past, very rarely has data been collected to answer specific, strategically led questions. Rather, the business tries to answer these strategic questions using what is available to them today (if data is used at all). This could result in flawed decision making based on incomplete information.

By flipping the perspective, decision makers could consider the big questions that they need answers to and ensure they have the right data points, analysed in the right way, to inform this decision correctly.

4 – Get the best analytics you can afford

Most commonly, organisations believe they can most dramatically improve decision making by introducing a greater ability to analyse data. A lack of the right skills and tools can result in the issue where statistical techniques are not applied with the necessary rigour to produce trustworthy analysis.

Companies may want to start by looking at their hiring policy. Are they looking for people with the required analytical skillsets required for tomorrow’s decision making, or people that have been successful in the past? There are lots of ways to get great analytical skills into the team, but it starts with making it a core requirement. Companies will benefit greatly from increasing the proportion of data scientists, data analysts, statisticians and all-round mathematical whizzes in their organisations.

5 – Reward those that trust the data

It is human nature to have a strength of one’s beliefs, to the point where arguments are made to discredit data that opposes these beliefs. Ensuring decisions are based on hard data, rather than gut feelings is key. 90% of us will not just accept data at face value when it contradicts our gut, so we need to put structures in place that prevent us from ignoring the data when it could help us make better decisions.

Decision makers should be rewarded when they show that hard data and detailed analysis was used to reach a decision. Revisiting decisions to look at how the data supported or contradicted the decision should lead to greater trust in the data. Greater trust in data will reduce our reliance on subjective beliefs.

Let’s accelerate progress with data-driven cultural initiatives

It is great that despite their challenges in becoming data-driven, 62% of firms have achieved measurable results from Big Data and AI investments. It is also encouraging that firms recognise that the blockers are 95% cultural – people and process – and only 5% technological. A strategic pivot that focuses Digital Transformation initiatives on solving cultural blockers, rather than simply introducing new technology, will surely help to accelerate progress.

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