Machine Learning a synonym for the induction of artificial intelligence algorithms with just about everything that has to do with data, is the next evolutionary step in the digital transformation of the world, as a whole.

While from a modernity point of view it may be seen as desirable to get with machine learning and accelerate corporate processes to integrate its methods, what really makes it imperative is the sheer accumulation of data that is already occurring naturally.

In the automotive industry connected cars can produce up to 25 gigabytes of date for every hour of operation. A Digital Universe study, sponsored by EMC, recently predicted that by 2020 there will be 5,200 GB of data for every man, woman and child on the planet. Even if your company is doing fine at the moment, ambling along on the quality of its legacy processes, it is clear that the road it is travelling on is changing under its feet.

When data informs every decision and is baked into every product hoping to wing it on legacy processes that worked last century is a strategy that is doomed to fail. More than that its faults will become apparent at later stages in the production or sales process where they adversely impact the bottom line. By then the wiggle room for experimentation and innovation will have disappeared and you’d be facing the “back against the wall” syndrome where every action as well as every inaction will be critical to the company’s future viability.

Data Mining and Customer Relationships

There are of course ways out of this. Companies that look at this changing roadmap and understand its challenge are already repositioning themselves to take advantage of the new deluge of data that they can now tap into and see the new patterns it reveals. In the not too-distant past, marketing personas allowed a company sales director to create marketing campaigns that passably addressed the personality profile of the company’s targeted audience.

This led to a sense that the company understood customer needs and it created a connection with its audience which is how it found its customers. The better representative of its potential customer the marketing persona construct was, the closer was the connection and relationship between the company and its public.

It was all guesswork of course, but it was also a technique that worked well enough when customers were pigeonholed in narrow demographics and had access to relatively few channels of information. This no longer works in an age where customers are more mobile in the classification they inhabit and expect the companies they deal with to have at least as much access to data devices as they themselves do.

This is why the change is really happening. From Amazon’s relatively faceless always-on, online presence to car manufacturers running massive, largely robotic factories, to driverless cars, to mobile phone companies, to supermarkets data mining is changing the understanding of the customer relationship and it is creating companies that are more responsive to customer needs.

When we have the data necessary to truly understand what a customer needs we are then in a better position to also predict when they would need something and why. That’s when the true magic happens.

The transformation of companies in this new landscape takes a form that looks a little like this:

  • Data with everything (every decision as well as suggestion is now backed by data as opposed to hunches)
  • Data flows freely (there are no more silos within the organization. Departments collect, classify and share information across the whole company. The company collects, assesses, classifies and shares information that is valuable to its customers, with them.)
  • Usability informs everything (when there is data available, everything that is implemented has a clear reason for its implementation. That includes products and services).
  • Data is a connective thread (It directly links a company’s intent and mission with the needs, wants and intents of its customer base).

The biggest change the incessant data flow makes imperative however is the one that is perhaps the least visible: In order to adapt and evolve companies need to change internally. Their internal structures of command and control, trust and responsibility have to transform into more interconnected ones that closely mirror that of their client base. Those that fail to grasp this and try to apply data mining as a patch to an existing legacy structure will not be around to see the end of this century.

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