I have been working in analytics for over 20 years now. One of the most frustrating things I have seen over this period is the relentless pursuit of and excessive focus on executive dashboards. Please don’t get me wrong, they play a role in business. A concise and crisp visual representation that provides the executive with a quick and easy way to view the company’s performance in real-time – now how can that be bad for business?
Executives love (and I mean LOVE) dashboards. I see the Single-screen “snapshots” when I go for meetings with COOs. I see them on the airplane tray table next to mine when I am hovering over AuNZ yes, I do peak every now then. I see those matt and glossy 13” screens depicting operational processes, marketing metrics, KPIs visually elegantly.
I do see the value. The value of just-in-time views of what is working and what is not. No need to wait for weekly and monthly reports. One scan of the all-telling dashboard and the executive has the transparency at hand and the opportunity to make rapid adjustments.
But dashboards have their associated issues. They describe existing phenomena or shed a strong light on the past occurrences. They do not predict, with robustness, future events based on past data and they cannot prescribe a course of action. There is often a significant amount of translation from the actual operational processes to what the executive sees – this is often done in excel or other manual tools meaning the information is only a partial view of the truth and in some cases can be wrong due to errors in manual processes.
The issue I have with dashboards, is the focus. The focus of executive dashboards is driven by the fact that the executives are the ones paying for the analytics program and by “HIPPO” decision making – as illustrated in the cartoon. Another reason is that the cost per person of executive dashboards can be too high due to license and pricing structures of most analytics solutions.
And this leads to the emergence of a few challenges;
The ‘Positional’ challenge:
Every dashboard is built on a set of priorities about what is important. This importance generally comes from the C-Suite’s opinion of what is important. Worse still, sometimes the priorities are defined by IT, a design expert, or a consultant who deploys the dashboards and does not know the company well enough. I have also seen dashboards that take into account measurements provided by the dashboard software vendor – nothing to do at all with the business. Companies end up with views into data that does not align with the business’ priorities.
The ‘Contextual’ challenge:
Often, we think of analytics as a representation of unbiased truth. We equate “empirical” or “quantitative” with “objective.” This leads to executives tracking and even acting on metrics simply because they appear on a dashboard. And we all know that dashboards don’t lie (insert a smile). There is a plethora of ways to present data. Context comes into play.
The ‘Causal’ challenge:
Plausibly the most significant issue with executive dashboards for decision making is attributing causality to elements that are merely correlational. Comparisons are the fuel that keeps dashboards burning. Executives compare performance by region, by month, customer inquiries by channel etc. They end up interpreting the groupings in a dashboard as causal when they may not be.
As I stated above. I am not opposed to the idea of an executive or the C-Suite leveraging dashboards. They bring value. As long as their limitations are kept into account when decision making.
However, there is an alternative. A focus on operational decision making. Fact is, in today’s rapidly changing business environment and increasingly complex business landscape, one person or a group of people cannot make decisions in vacuum. An organisation’s performance is now the net result of each and every decision, made by each and every staff member, irrespective of seniority, representing each and every business unit function and across the entire organisation. Yes! That is what leads to performance today.
If businesses can improve the operational decision making of the organisation (and continuously improve it), then the organisation can benefit from better quality of decision making and its results flowing upwards to the C-Suite. This leads to the executive suite making better decisions based on more accurate and more valuable information. Result – significant improvement in bottom-line results.
I will share a concrete example from the Australian business landscape with you. A customer of ours went through a private equity transaction about 18 months after we implemented a very strong operational decision-making program. After the transaction was complete, I had an in-depth conversation with the CFO of the firm. I wanted to gauge the impact of the operational decision-making program we had implemented. The CFO shared with me that they would not have been able to do the transaction if they did not have the analytics system we implemented, in place. He said that his team was able to confidently and quickly respond to every request that came from the private equity team because the data and information were coming from the front-lines.
To deliver operational decision making there are a few things a business must focus on, pervasive use of information for decision making, consistency of usage across business units, and a focus on the frontline decision makers, not management or executive decision making.
Focusing on pervasive use allows the business to account that frontline decision making is often more complex and nuanced than we would like to think or give credit for. Therefore, we need people backed by good information making good decisions to drive our bottom line results.
If the front-line decision making does not require the level of complexity, the business should look at automating that job in some manner. The data processes that allowed traditionally, a person to make good frontline decisions can be reused as the first step towards automating the process or job. We are seeing this called – robotic process automation (more on that later).
We find this approach works best in environments with large amounts of capital and/or many people making daily decision making. Industries like financial services, retail, manufacturing, universities, and healthcare all fit this bill.
Let us know if you’d like to discuss how we can help you improve your operational decision making.
Zachary Zeus is the CEO & Founder of BizCubed. He provides the business with more than 20 years' engineering experience and a solid background in providing large financial services with data capability. He maintains a passion for providing engineering solutions to real world problems, lending his considerable experience to enabling people to make better data driven decisions.