Christophe De Greift explains why now is the time to plan your analytics transformation, why you should, and the first step to take.
Artificial intelligence is a relatively young discipline in companies and in constant evolution. However, the experience of pioneering companies in various sectors and continents confirms their high value generation when accompanied by a true transformation of the company. Those who have not yet internalized their analytical transformation plan should start now to be able to arrive on time, as I explain below.
Being analytical is increasingly necessary to stay competitive
Many important business decisions are better when supported by data. Neuroscience has recently confirmed what common sense has always allowed us to understand: man can be irrational, biased and even blind. The machine is not 100% reliable either; the key is to precisely define the role of man and machine for each decision, as explained in a previous article . In very repetitive problems such as forecasting the demand for mass consumer products in retail stores, the most advanced and successful companies limit human intervention to exceptional cases. In more sensitive problems such as medical diagnoses, the radiologist is assisted by artificial intelligence.
Across all sectors, the competitiveness gap between analytics pioneers and the others is growing, threatening the sustainability of the latter. Those who have succeeded in analytics redouble their efforts and investments to become even more analytical, creating the virtuous circle explained in a recent MIT and BCG article.
Being analytical requires a transformation at the people, organization, processes and technology level.
Key points include:
- Data as an opportunity
- Predictive maintenance
Read the full article, 3 reasons to plan your Analytics Transformation now, on christophedegreift.com.
Jason George uses the evolution of the aviation industry as a means to explore the cost of risk aversion and how it can stymie growth.
Building in every possible contingency as part of a strategy can end up producing something so encrusted with extraneous elements that agility is compromised. Alternatively, it may hew so closely to known and safe paths that it ends up losing the novelty that would make it compelling. If you can’t cut yourself loose from a certain strategy or mental model, your degrees of freedom become limited. In the process new paths are closed off, even though they might unlock a different way of operating. Sometimes caution is a crutch whose real costs are not adequately calculated. A better path might involve getting rid of the safety net.
When faced with ambiguity too often we choose the guaranteed loss, which might be greater than the as-yet unknown costs of taking the riskier path. The safe route may be comfortable, but it is costly.
Points explored include:
- Contingency as part of a strategy
- Product cannibalization
- The cost of the safe route
Read the full article, Calculated Risks and the Costly Status Quo, on Jason’s website.