Recommending Deep Learning for Your Company

Useful outline.  With cautions.

Should You Be Recommending Deep Learning Solutions in Your Company?    Posted by William Vorhies 

Summary:  If you are guiding your company’s digital journey, to what extent should you be advising them to adopt deep learning AI methods versus traditional and mature machine learning techniques.


By now everyone is at least familiar with using AI/ML as a required cornerstone of company strategy.  Frequently this is referred to as ‘digitization’ or the ‘digital journey’.  There’s plenty of data showing that early adopters who have gone all-in on this approach are already pulling ahead of competitors both in share and bottom line results.

There’s also mounting evidence that even though most companies are now aware of this need, either their planning or their execution has been half-hearted.  We are on the upswing of this movement and like many previous revolutions in technology and management, the leaders are pulling away and the rest of the pack is about to get a wake-up call.

So as a data scientist in these companies, you are increasingly likely to be called on to participate, either by leading or supporting the teams assembled for specific projects or for the formulation of the broader strategy and the prioritization of projects within that effort.

The Problem with ‘Digitization’

The problem with ‘digitization’ is that this naming convention seems to focus on the data (good) without adequate understanding the very many advanced analytic techniques from which to choose (bad).

Thinking back to previous breakthroughs in technology-driven performance improvement like reengineering or Six Sigma, we all understood that there were fairly safe and mature techniques with reasonably predictable outcomes versus bleeding edge techniques that promised extraordinary outcomes but came with extraordinary risks.

We’re in a very similar place today regarding which data science tools should be applied to which projects.  Although data science projects and the whole digital journey has become a team sport with many different types of participants, it’s likely that only you, the data scientist, will have a grasp of the risks versus the rewards of different tools. ...."