Doubling down on double standards - why won't organizations practice what they preach when it comes to data-driven decision-making?
- Organizational platitudes about data-driven decision making aren't matched by what's really happening in the business world.
Earlier this week, Neil Raden asked the highly-pertinent question, ‘Is the data-driven enterprise an oxymoron?’. He observed:
Business decisions aren't science. It's a provocative assertion. It goes to the heart of the current proposition that companies need to be data-driven. What is a data-driven company? There are many ways to define a data-driven company, but the consensus is one which makes strategic and tactical decisions that are rooted in data analytics.
Hot on the heels of this analysis comes some new global research from Salesforce with the provocative claim that:
Seventy-three percent of business leaders believe data reduces uncertainty and drives better decisions - so why aren’t they using it?
Silver bullet incoming
It’s a good question, if not exactly an original one. In over three decades covering the tech sector, it’s one that’s been raised, in one form or another, with depressing regularity, usually accompanied by a pitch for the latest ‘silver bullet’ that’s going to be put an end to the situation.
Given the advances in analytics tech that have taken place over those decades, it might be hoped that things had progressed further than they appear to, at least according to the Salesforce poll of “10,000 business leaders”. But in fact, while 80% of respondents are happy to state that data is critical in decision-making at their organizations, putting this into practice falls considerably short of the importance that it theoretically carries.
For example, over two-thirds (67%) of global respondents are not using data to make pricing decisions in line with real-world economic conditions. Given the turbulent nature of the worldwide macro-economic climate, that seems like a missed opportunity today more than ever.
Meanwhile less than a third (29%) use data to inform their strategic planning for entering new markets, only 21% use data to drive decisions around diversity and inclusion policies, while a mere 17% base determining climate targets on hard data, this last point despite the near universal protestations of organizational commitment to sustainability initiatives!
The findings inevitably vary on a country-by-country basis. So in the US, 37% of respondents say they are data-driven when it comes to deciding on pricing, whereas that falls to 34% in the UK , 30% in Germany, 28% in France and a mere 16% in Japan. Respondents from Brazil and Singapore seem the most practical here, with 41% each basing their pricing decisions on data.
As for those sustainability commitments, the UK on 19% and US on 18% are ahead of Germany and France on 15% and 14% respectively when it comes to using data to inform climate strategies. Meanwhile a miserable four percent is the best that Japanese respondents can come up with. No particular group of national respondents comes out particularly well here, so let’s bear that in mind the next time we hear platitudes about how important it is to have robust sustainability strategies in place. Guesswork isn’t robust data-driven planning.
On a wider note, is it a case of double standards in play when it comes to the clear divergence between what business leaders say and what they actually do, when it comes to tapping into data to drive often critical decisions?
All the right words are being said, in pretty much the right order, to tick all the right boxes. Seventy-three percent of all respondents agree that data accelerates decision-making, as well as helping to make more accurate decisions, while an equal number say it builds trust. Two-thirds see data as useful to counter personal opinions/egos in business discussions, while 72% say it helps keep people focused on things are relevant to the business.
All that being said, these responses just bring us back to a crucial question - why aren’t organizations practising what they preach?
Overall, the global respondents cite three major blockages. Firstly, lack of understanding of data, cited by 41%. Secondly, an inability to generate insight from data. Thirdly, there’s just too much data to cope with, 30%.
Of these, the lack of ability to understand inevitably loops back round to that other seemingly never-ending challenge of the lack of available skills, which in turn reflects the impact of years and years of national government policy on this topic, and the strength - or otherwise - of the current educational system.
For example, nearly half of UK respondents (49%) talk about their lack of understanding of data, while just over a third (34%) have problems tapping into actionable insights. In the US, while 42% of respondents cite lack of understanding of data as an issue, less than a third (30%) point to inability to generate insights. In contrast, 38% of Indian respondents lack understanding, while 37% say they lack insight generation ability, while comparable percentages in Japan are 31% and 28%. The benefits of a more tech-savvy, skilled-up talent pool, perhaps?
But it’s the third category of having too much data that particularly catches my eye. This is particularly an issue for respondents from France (36%), Germany (35%), the US (34%) and the UK (34%). The Salesforce report repeats the oft-cited prognosis that the amount data being generated will more than double by 2026, with the underlying message that this situation is only going to get worse.
That may well be the case, although again this is the latest iteration of a long-running theme - drowning in data. This goes back, it seems to me, to a basic human instinct to want more and more and more. Combine that with the dark underbelly of office politics and executive rivalry - I’ve got more data at my disposal than you, so I’m more important than you! - and you end up accumulating so much data that you can’t see the metaphorical wood for the trees.
This is nothing new. It happened with early Business Intelligence. It was endemic when data warehouses were all the rage. And now that analytics tech has evolved to its current degree of sophistication, it’s going to be happening again. It’s basic human greed and it results in organizations being blinded by the data that ought to be enabling them to see more.
Something's got to change.
At the macro-level, governments need to be putting in place policies and practices that enable countries to grow their own data-skilled talent pools.
At the organizational level, businesses need to play their part and make sure that their workforces have the opportunity to develop and enhance their digital skills.
And at a data-greedy exec level, we all need to learn to say, ‘No!’. Just because there’s more data on offer, doesn’t mean it's good for you. Less can very often be more. Quality, not quantity, is key to what data you need.
You should also, if you haven't already, check out Peter Coffee's excellent ruminations around the idea of data-driven decision-making, which can be found here.