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LSA – Towards an acceleration of digital transformation and analytics to face a decelerating world

By 16 November 2020 No Comments

It has been several months since the current health situation took the whole world by surprise, drastically and lastingly modifying our habits as well as our consumption patterns. In celebrating the transition to the new year, we never imagined having to be confined to our homes the following March, and yet more than half of the world’s population is now affected by these measures. Everyone agrees that the unprecedented situation will profoundly transform our society, but few can really predict at what level these changes will really take place.

But what are the impacts at the level of companies and the challenges they have been trying to overcome for years on their digital transformation? According to a study published a week ago by Forrester, titled “In Digital Transformation 2020, It’s Time To Catch Up To The First Movers,” the research firm found that only 15% of companies surveyed in North America and in Europe was “advanced” in terms of their transformation. What impact does the health crisis have on the 85% who have not yet completed their transition? There are many changes we can already anticipate, especially in future analytical models, to enable businesses to adapt – and survive – in the post-Covid world.

 

The health crisis has accelerated the questioning of the two main analytical models.

Currently, we can categorize the analytical business model into two main categories. First, many large companies still use the traditional approach, with cumbersome solutions that manipulate data over a long cycle but with the advantage of not requiring large financial investments. This is the case of the major historical players in mass distribution who analyze the evolution of their customers’ consumption trends every week. Conversely, the pragmatic approach, more implemented by “digital native” companies, offer high performance and rapid solutions, making it possible to analyze a large mass of data over short cycles but requiring a substantial investment. Ridesharing service applications provide a perfect example, requiring as close to real-time as possible a look and analysis to meet the needs of their users.

Without finding a perfect solution combining the best of both approaches, CIOs were coping with this situation as best they could, hoping to gain some time in their digital transition to find a more satisfactory answer to the situation. But that was without counting on the current crisis, which is about to overturn existing patterns.

The health emergency calls into question all the existing chains. As the professional world adapts its day-to-day operating methods to changing circumstances, traditional businesses can no longer afford to wait for their data to be analyzed on a weekly basis in a world where every day brings its share of novelties and uncertainties. What to do then? Close a site or place employees on partial unemployment? Traditional models cannot answer these questions in less than a few days. It then remains to make decisions intuitively and hoping to limit the damage.

Pragmatic models are in theory better prepared but suffer from an IT infrastructure that is far too expensive to cope with the situation. In order to be able to keep the jobs of their employees as much as possible, some native digital companies have found themselves obliged to stop their analytical chain in order to keep the maximum budget essential to the survival of their company.

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Source : LSA, Emmanuel Dubois

Language : French