It is often spoken about, marketed, presented and written, that analytics helps with making better decisions, more accurate and timely decisions and almost every other combination of 'better, faster, stronger' words. I set to thinking about this a little more, and went back to the basics of how individuals and groups make decisions.
If you have ever had the pleasure, or displeasure, of group dynamics or organisational behaviour, you may have heard of the rational choice model of decision making.
I also noted from Vince's post a discussion about the merits of high performance analytics in the so called "big data era" that high performance analytics can be for everyone, you just need to know how to fit these technology advances into a process and see why they add value.
The underlying concept is that individuals, societies and organisations are trying to maximize their utility while minimizing the effort required, or more simply put maximum outcome for minimal costs.
The model assumes there are six steps in the decision-making process.
- Define the problem.
- Identify decision criteria.
- Weight the criteria.
- Generate alternatives.
- Rate each alternative on each criterion.
- Compute the optimal decision.
It's nice to have a great theory, but we all know the problem with a great theory is that reality is different. So the real crux of this post is to get to the issues in decision making and how high performance analytics can help.
When it comes to improved decision making and our current state, most people and organisations are satisfied to have an acceptable or reasonable solution rather than an optimal one. Most people, when faced with a complex problem, will reduce it to a level which can be readily understood. This is often due to the limited information processing capability that we have to assimilate and understand all the information needed to optimize.
So this is where something like high performance analytics can help. Not only have people long had limited information processing capabilities, so have machines. Now with these game changing technology advances in software and hardware platforms, we can now manage all of the data, all of the time, assimilate it and process it to an optimal outcome in seconds or minutes rather than hours and days.
Now it is possible to optimize. In fact you could ask the question, “What's your excuse for not taking all information into account?”
One thing that is not considered is the time value of money, well at least by marketers. The concept that “a dollar today is worth more than a dollar a year from now” so therefore the financial benefit of making a faster decision that impacts the financial position of your organisation is critical.
The best thing about all of this is that the use of analytics is being continually proven to add to the bottom line of business.
Our research has found a shift from using intuition toward using data and analytics in making decisions. This change has been accompanied by measurable improvement in productivity and other performance measures. Specifically, a one-standard-deviation increase toward data and analytics was correlated with about a 5 to 6 percent improvement in productivity and a slightly larger increase in profitability in those same firms. The implication for companies is that by changing the way they make decisions, they’re likely to be able to outperform competitors.
Professor Eric Brynjolfsson, Schussel Family Professor of Management Science at the Massachusetts Institute of Technology’s Sloan School of Management, Director of the MIT Center for Digital Business, and one of the world’s leading researchers on how IT affects productivity.
Analytics and optimal decision making go hand in hand. It's time to move away from poor decision making habits, from past experience, what we know in our sphere of knowledge, to avoid the apparent inconsistency of not sticking with a previous course of action and High Performance Analytics is the answer.
The ability to improve decisions leads to innovation – join us next week for a discussion about that very topic.
So what is stopping you from making decisions based on all of the data, all of the time, at the speed of right?