Decision making around the world has evolved, Governments, Private organizations have now added analytics and Artificial intelligence into daily decision making. The outcomes have been near perfect decision-making that leads to progress and growth.
The current situation in Nigeria, practically shows that decision-makers are either using archaic experience to solve issues, or refuse to utilize available insights from analytics to make their decisions.
Imagine the sliding Value of the Naira and the recycled approach to managing it, it is almost predictable that every time there is Government intervention, the value goes down further negating the reason for the intervention in the first place. We all know the law of demand and supply, scarcity and availability but what we should know now is that with analytics the law can slightly be adjusted for better results. Old economics Training will tell you if a good or service is scarce and demand is high the price of such will go up, but when a good or service is available and demand is low the price will come down considerably.
Put analytics into this mix using historical data, you will have the law explained further like this, if goods become scarce from the base case by 10%, and demand increases by 20%, the price of the goods or service will go up by 20%. With this new information, any ban on goods or services that will make it scarce will be totally avoided because you can predict the hardship this will cause by prices of goods and services going up by a whopping 20%(Proactive decision making instead of reactive).
Imagine we have no information on the predictive outcome of our action; we just wake up and roll out a new policy pushing people further into hardship our intention was good but we were blinded to the analytics balloon effect such a policy will have(Every action has a corresponding re-action elsewhere).
Analytics and AI bring so much clarity to decision making helping us see the predictive effect of our actions, we can then with the analytics information decide to look for equilibrium, where scarcity and availability push prices just up by 3%, minimizing the impact on the people, this could mean instead of banning the good, we put a tariff on such goods, not too high to make it scare and not too low to keep it at the current state, Just somewhere in the middle (a position reached based on testing done not an assumption or past experiences)to achieve our desired aim.
While analytics can give us predictive results in the line we were thinking, its greatest power lies in showing us patterns that are totally against conventional knowledge, and here is where it shines. The analytics technology can discover patterns in data that humans find difficult to see and this helps the individual make a better decision. An example of this is the use of analytics in managing pre-term babies in a global hospital. The hospital experts know that when the vital signs of babies stabilize then it is time to move from ICU and Doctors can rest! But this conventional knowledge was put to test in pre-term babies and full-term babies, and the result came out differently.
When the vital signs of the Full-term stabilize, the baby’s are on their part to full recovery, but when the vital signs of the Pre-term babies stabilize they are on their way to being hit by an infection in the next 24hours. Imagine the Hospital relies only on conventional wisdom or archaic wisdom on vital sign stability as a measure of progress on babies, many preterm babies will ultimately be moved out of ICU and might die from infection in the next 24hours due to the assumption and use of archaic medical science wisdom not considering analytics in their decision making. (The Standard operating procedure of the organization was updated due to these findings).
Whether as a Bank Manager, Health Care Professional, Government official, Security expert ETC, your decision-making must be a mix of analytics and experience. Historical data on the goal you want to achieve is needed to predict the outcome, with the prediction in place, your experience is now needed to make a decision on what to do to avert the negative outcome predicted or how to get the most from the positive outcome predicted. Finally remember, DATA DOESN’T MAKE DECISIONS, HUMANS DO.
