In an earlier piece, we touched on the challenges faced by decision-makers in today’s big data world, reminding ourselves of the importance of getting data governance right, even before such joys as augmented analytics hit our dashboards. Putting to one side the issues of optimizing the underlying data, we’re looking today at how executives interface with that data… and whether they prefer to pivot their tables or just want some time to think.

Excellent Excel!

We’ve seen Microsoft’s Excel software used as the basis for reporting in many companies we’ve worked with, but, frankly, using Excel for reporting in a Big Data environment is like serving kopi luwak (civet coffee) in a paper cup. Indeed, a Journal of Accountancy reader wrote to the publication earlier this year to comment that their company not only uses Excel for financial reports, but then then converts them to PDF format before they go up to the executive team. This is, presumably, a method taken to remove the risk of a user accidentally compromising the data shown. The J of A publication comments that it would certainly be preferable to use Excel as the ideal file format, and goes on to outline many of its features and best practice for formatting data for report presentation.

Reports provided in an Excel-based format allow recipients more flexibility to prepare what-if analysis computations, create charts, and build PivotTables, among myriad other possibilities.

But seriously, at an executive level, is this really going to happen?

Visualizing a dashboard

While Excel may still be the software of choice for accountancy professionals (it has its own category on the J of A website…), the options for bespoke management reports – ie those that report operational figures – are broader. There are hundreds of companies offering data visualization tools, which purport to allow easier access to insights hidden in large or varied data sets that might have been hard to dig out from sheets of data cells. Indeed, the ability to view and play around with graphical representations of data offers a number of benefits, as explains:

  • Visualised data is processed faster (based on research that the human retina can transmit data at approximately 10 million bits per second)
  • Data visualisation supports visual learners (who make up approximately 65% of the population)
  • Visualisation provides actionable items (graphical reports acting as motivators to sales teams, for example, or insight into developing trends).

Dashboard software is as equally prevalent as data visualization tools, and the two are regularly combined, with dashboards displaying an organization’s chosen key metrics in a visual manner (very often sourced from multiple systems). Many offer large amounts of flexibility, enabling the user to slice and dice the data to look at segmented information and to develop their own displays. But while this personal configuration might be the stuff of business analysts’ dreams…

… seriously, at an executive level, is this really going to happen?

Indeed, research by the Economist Intelligence Unit showed:

Executives are more constrained by their ability to analyse data than by access to data itself.

It should be noted that the experience can differ between mature and developing markets. In the former, lack of data is not perceived as an issue – the challenge is analysing it correctly and with new techniques. In developing markets, often just getting hold of reliable numbers in a timely fashion is still a challenge.

Thinking fast and slow

The EIU’s research shows that the issues around good decision-making are not just about skills (in data analysis and decision making) but also cultural. Executives want an environment with accountability, collaboration and transparency. In agile organizations, it’s about allowing employees to ‘fail fast’:

A hallmark sign of today’s effective leaders is his or her ability to unlearn old habits and change their mind when presented with convincing evidence. For example, people are used to a culture that doesn’t tolerate failure, but failure is an essential ingredient for radical innovation. We need to encourage others to fail fast and safely. Then we need to glean lessons learned and disseminate the learning throughout the team as soon as possible.

Equally, though, there can be value in taking some time. An interview with Bernhard Günther (then CFO of German utility RWE) outlines some of the efforts made in the firm to consciously root out bias in their decision-making, after years of multi-billion dollar investment in conventional power generation in a world that was quickly turning towards renewables (always easier to see in retrospect). These techniques involved the creation of devil’s advocates, consideration of radical scenarios, and conducting ‘premortems’:

“Imagine we are five years into the future, and this whole project we’re deciding on today has turned out to be a complete disaster. What could have happened in the meantime? What could have gone wrong?”

He admits that to fully conduct an awareness and debiasing process is time-consuming, and applied to around 30% of decisions made within the company. So these decisions are not always made in a fast manner. But what the process tries to do is to think, pardon the cliché, outside the box: to imagine scenarios outside the norm; to expect the unexpected.

Good decision making is, therefore, a function both of the organization’s culture and the data available for consideration.

At LigaData, by doing our bit to help organizations get the right information they need from their systems, displayed in the most usable way, we’re freeing up time for executives to stretch their thinking and work with their colleagues to make grounded, useful decisions.

What do you think? Is it data or culture that’s more of a challenge to good decision making in your organization? We’d love to know.

Further reading: