A Philosophy For Business Decision-Making: An Analyst’s Brief Guide
Philosophy can be described as the study of what ought to happen. This of course is different than what does happen. This struggle between ought and is has consumed the greatest minds, from Plato and Aristotle to Kant, Descartes and Russell. I will not even begin to touch on the metaphysical, the deontological, or the normative theories of the human experience. But I do want to briefly outline a personal philosophy on analytics in business, or what ought to be in the decision-making framework for every business. Here are the basic tenets.
Data should be the objective foundation of the decision-making framework, but don't under-estimate the subjective.
If you are not using data to make decisions, you are missing out on objective input that can inform your decision-making process. I do think there is a place for subjective (gut) decisions, but the foundation needs to be established with data analyzed objectively. The key is finding the right balance between expertise and objective facts. The former can drive theories and innovation while the latter offers a way to test ideas.
The information system should be designed to collect the right data correctly.
Collect all of the data you will ever need to make the important decisions about your business, but don’t get bogged down in trying to collect everything. Some data may not be relevant or actionable. Focus on quality. Any reporting and analysis can only be as good as the data that go into them.
KPIs should be targeted to your objectives.
It is easy to come up with dozens of metrics to try and measure performance. But this leads to information overload. Go through the process of identifying the critically important KPIs and focus on the handful of metrics that truly matter to your strategies and tactics.
Reports should tell a story.
Dashboards and periodic reports are loaded with numbers, charts and tables. But what is often missing is a narrative that answers the 4 critical questions . Actionable information comes from the presentation of data in context.
The analyst should analyze, not just report and fulfill data requests.
It is common for individuals with the title of “Analyst” to conduct tasks limited to finding data and populating reports. This is not analysis. An analyst provides value through insight discovery. If you’re an analyst that falls into this typecasting then push through this by adding more context and more insights when you publish and distribute your reports and data requests. If you’re a business leader with an analyst that fits this role then empower and encourage him or her to interpret and analyze, not just report.
To summarize my philosophy, the decision-making framework should be built upon a foundation of clean data balanced with expertise converted into actionable information via a robust information system and a strong analyst capable of uncovering and presenting insights that support informed decisions. Did I miss anything? What would you add or change?