Stack in the Chain

The pandemic has shown that strategic references can shift overnight rendering competitive advantages to be lost in one felling stroke. It has also shown that the so called well established frameworks within organizations will have significantly shorter life spans. Supply chain flow will get significantly impacted and organisations could get ‘stuck in the chain’. Words like institutionalisation will get extinct.

Four biggest pillars namely , maintaining customer relationship and retention , recasting strategies , sustaining supply chain flow streams and operational approaches will have to be constantly reshaped. Good news is that we are already significantly better placed in terms of technology and enormous computing resources being available through cloud.

However the reason for the floor getting swept under our feet is lack of preparedness as we are very slow in being data driven. It is not so much about resources as it is about our mindset. On one instance we as data scientist were presenting to the Board of a very large organisation. We were trying to bring out new perspectives of the business that seemed strongly directional through some effective visualisations . However a member of the senior leadership team almost exploded, as we were presenting something that shook his convention. The team was so used to seeing Excel charts and ppts, that even a bubble graph was extremely unsettling. Let alone the violin, swarm , cat and. the boxen plots being offered by packages like Seaborn.

We have to get data driven. Data Science is the ‘full- stack in the chain’ that will fully complement the businesses seeking very sharp and agile solutions to the problems faced everyday. We have to move away from the traditional BI tools and get used to looking at discerning visualisations as single most important component of our dashboard. We should not be looking at numbers that all. They are already in the background presented through powerful visualisations. Models such as xgboost and random forest ,will give us deeper insights and plethora of perspectives most accurately predicting the next shot to be taken .

But they have to be stacked up on the visualisation ladder sequentially to appreciate the clarity in the direction we choose. We have model interpretations to prove why the solutions are what they are. Pandemic has shown that there are extremely radically changing customer needs never imagined before and what could have been thought as utopian in the earlier context. What sounded utopian yesterday is a reality today and only stacking up the chain with data, modelling studies and state of the art visualisations can get our legs back on pedal.