Douglas Hubbard – How to measure anything
A lot of Fermi-type deconstruction of drivers, Monte Carlo simulations, and value estimates .
Douglas Hubbard – How to measure anything
A lot of Fermi-type deconstruction of drivers, Monte Carlo simulations, and value estimates .
How to assure that insights change business decisions
The Board has decreed that you have to become a data-driven organization. To avoid obsolescence, things need to change. The old way of doing business is no longer viable. Only Data can make you smarter.
So, there you go. An Analytics department is set-up. A Big Data platform is is put in place. Data scientists are hired. Models are fitted. Insights flood the organization. And after a while all graphs start pointing to the top-right corner. Right?
Nope: Sales wants to sell, Operations wants to operate, and Marketing wants to do whatever it is that Marketing wants to do. No-one ever wants a proper analysis. Especially if the outcome is likely to challenge the status quo. There is a shop to run, a client to manage, and a problem to fix. If Analytics does not directly help to do just that, it is deemed useless. And everyone who does not get that, frankly, does not understand the business. That’s how, in many organizations, Data is side-tracked.
The first priority, is of course to assure that your insights are relevant and focus on improving key business decisions. But that is not enough. These insights should actually change the decisions your organization makes. And frankly, many business owners are unable to take an impartial perspective with respect to unexpected challenges – especially when under pressure.
What is needed, is someone who can ensure the fact-based perspective is taken into account in decision making.
Someone needs to defend data-driven insights without looking for compromises from the start. Someone needs to be in a position to challenge Category Management on their Sales v. Margin trade-offs. Someone needs to hold firm on the risk assessment in the face of an exciting Sales opportunity.
In short: you need a Data’s Advocate.
That is not to say that Data should always prevail over ‘Gut’ or ‘Experience’, or ‘Entrepreneurship’, or whatever you call it. But the trade-off should be an explicit one. Both to assure better decisions, and to build awareness on what it means to be a data driven organization.
The brave attempt to cover an inherently deep subject in a non-technical way.
Sound Math +Dubious Incentives = Potential Trouble
An overdose of righteous indignation makes the writing less compelling.