Digital Shift & Accelerated Disruption. Episode 3: Management 3.0, a mindset revolution from the C-Suite to every level

Digital Shift & Accelerated Disruption. Episode 3: Management 3.0, a mindset revolution from the C-Suite to every level
In a previous article about applying a Minimum Viable Product approach from a startup environment to established companies contexts, I opened the subject at the end of the article on the issue of decision-making in established companies and how it could be a challenge to go fast. So let’s talk this time about this issue of decision-making, hence management.
Going digital means a lot of things, from technological to business transformations, impacts on processes, organizations, etc… What is the bottom line for any company which takes the path of digital transformation? It’s to survive by adapting and having the capacity to move as fast as its competitors, especially disruptive newcomers who have the advantage of “no legacy” to slow them down. Speed is key, in an uncertain and complex environment, and this is a whole new challenge for management of large organizations: if your organization scales up to 1000, 10 000 or 100 000 people and has 5, 10, 15 or more levels of management, how can you ensure that decisions taken at the top level management will be taken into account… especially if these decisions may need to change rapidly to cope with accelerated changes on the market? Well, you can not.

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Digital Shift & Accelerated Disruption. Episode 2: Transforming your legacy IT systems from Titanic to speed boats

Digital Shift & Accelerated Disruption. Episode 2: Transforming your legacy IT systems from Titanic to speed boats
Legacy IT systems often have very poor time to market, it can take many months (or years) before an idea may be effectively implemented and rolled out in production. Legacy systems are often monolithic applications which are costly to be deployed in production, because you need to make exhaustive non regression tests on the whole perimeter to ensure quality, you need to perform lots of manual operations to deploy the application from an environment to the other… In this context, you can not afford to deploy just a small evolution (which you are not sure will not have a side effect somewhere else in the application, hence the full non regression testing) at this cost.
That’s why your best option will be to make big versions with lots of new features to optimize the cost of testing the whole application, the deployment cost, etc… and consequently, this big version will take months before going in production as there will be lots of work to do.

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