When I was recently making my way through Istanbul to meet my wife for dinner, I was using Google Maps to take me on the fastest route through the evening rush hour. My wife was waiting at a gallery opening in Nişantaşı in the European part of the city and I was coming from Sancaktepe on the Asian side and had to cross the Bosphorus on one of the bridges (or using the Avrasia tunnel).

As the sat nav system kept updating me in real time on my estimated arrival time, on traffic conditions and expected delays on my current route, showing me with different colors the alternative routes, I thought to myself: this is real risk management; relevant information presented to me, the driver, at the right point in time and space to make informed decisions, while showing me the impact of different choice alternatives on achieving my primary objective (arriving at the right location in time to meet my wife) under defined policies (shortest route, fastest route, avoiding toll roads …) and current, real-time updated traffic conditions.

I recalled having used the cockpit of a car as an image for risk management workshops in the past. There are the different gauges for speed, engine revolutions, cooling water temperature, fuel level; there’s outside temperature, warning lights for critical system components like the battery; tyre pressure control; unfastened seat belt warning, warnings for open doors or trunk; distance sensors and so many more.

All in front of the driver to give the relevant information at the right time to make a decision. Some of them are purely informational, like the odometer, remaining estimated distance with available fuel, time, temperature.

Some of them are coupled to automatic risk mitigation actions, like the windshield wipers upon detection of drops on the windshield, automatic front lights when it gets dark outside; warning sounds for opened seatbelts, proximity alert coupled to brake boosters; anti-lock braking system…

You can have automated compliance management systems like an optical recognition of the speed limit signs at the roadside and give you a warning when you exceed the limit; or you can limit the cruise control system not to accelerate beyond a set speed limit … and so much more.

But there is one thing that a car does not need: a heat map showing likelihood and impact of a common list of risks associated with car driving considering the incidents and performance data of the past 3 hours (or 300 km) of driving; being updated every 3 hours; maybe showing the driver that considering historical data, under current conditions (temperature, darkness, weather, speed, density of traffic) there is a “possible” likelihood of having a “moderate” impact accident.

At the end of the trip, I arrived safely and im time for the gallery opening and even found a parking spot nearby. Google had routed me off the congested main roads through tiny one-way alleys on the last few hundred meters which made all the difference between being in time or at least 30 minutes late. And thanks to all the different sensors in the car mentioned above, I managed to safely navigate the labyrinth of Nişantaşı and finally park my car in a tiny spot without any scratches.

If we don’t need them in a real-world, every-day decision-making context like driving a car, which is by accident statistics the most dangerous means of transportation, why do we employ heat maps in business?

Management needs information that is relevant to making informed, responsible, ethical – the list could go on – decisions to meet business objectives under complex, dynamically changing and ambiguous conditions. Heat maps – and in fact the entire current risk management processes (Risk Management 1, as Alexei Sidorenko denotes it) – do not meet these criteria. They are too much simplified – or in some cases even wrong and outright dangerous – to be relevant and useful for management.

Everything should be made as simple as possible, but not simpler. – Albert Einstein