When it comes to digital transformation, there are 4 root causes of failed digital initiatives:
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Data Infrastructure
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Data Infrastructure
The existing data infrastructure creates limitations when it comes to leveraging unstructured data to drive insights. Originally created to deal with structured data, this infrastructure wasn't prepared for the explosion of big data. The pieces are hard to change once defined since the addition of new data dimensions requires expensive design and reprocessing effort. Moreover, legacy data infrastructure makes it very hard to get to a deeper level of granularity of insights.
For example, when have you last seen a bank that is as precise at personalization as Amazon?
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IT Processes
Traditional IT deployment cycles as they're set up in many legacy enterprises are not designed to support and drive the modern analytics "test, learn, adapt" paradigm. These processes should be based on experimentation. If something has to fail, it has to fail fast. Instead, in a legacy enterprise, you have to first spend a lot of time doing the analysis and making sure you get it right the first time because if you fail, it may be fatal.
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Back-End Systems
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Back-End Systems
In most legacy enterprises, these systems end up being a bottleneck. They simply aren't designed to handle the probabilistic choice-based workflows to enable real-time responsiveness to customer signals.
Have you tried opening a bank account online? It's not possible precisely because, in most banks, their back-end systems are not able to support it and deliver real-time customer services online. As a result, businesses are unable to realize the true potential of tightly coupled systems and automation for real-time customer services and an end-to-end transformation.
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Legacy Business Processes
Legacy Business Processes
The basic mindset of these processes is all about control, risk management and being comprehensive. These processes were designed to get things right the first time without fail. As a result, businesses have built very complex processes to avoid failure, but as with anything very complex, it is hard for it to be fast in real time. The legacy mindset of the "Right First Time" process design makes it difficult to drive iterative experimentation-based improvements.
In other words, even if the technology works, business processes end up slowing things down.
In other words, even if the technology works, business processes end up slowing things down.
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Above is a summary of an article published in Forbes by Nitin Seth (ex-COO Flipkart).
Read the full article here:
Forbes.com/sites/forbestechcouncil/2020/01/14/maximizing-returns-from-digital-investments-part-one-why-the-problems-persist/#2d45b271cc95
