There is an old saying “keep your hand on the plow”. It was quite interesting to read about how this phrase came to be, and how it applies to business today.

Most of us pay little attention to tractors in a field as we drive past.  Yet it was not long ago that this task was done with a horse and plow.  Now I know you are thinking, what the heck does that have to do with business?  Plow the ground, plant the crop, tend the crop and then enjoy the fruits of your labor – sounds a lot like business to me.  Back to plowing – keeping straight rows and turning the soil the right depth is critical. A successful farmer knows to apply constant pressure to the plow.  Too little and the plow pulled out of the ground, too much caused the plow to go too deep and stressed out the horse and farmer.  Another aspect, if you look closely at old pictures, is that you will see the reigns of the horse tossed around the farmer’s neck.  If the farmer looked right the horse knew to pull right.  So if the farmer was day dreaming and looking around the result would be crooked rows.  Crooked rows wasted space and made it hard to care for and harvest the crops.  The farmer knew that to survive he had to keep a steady hand and look forward to get the best results.

Now we interpret this saying to mean don’t get distracted and don’t lose sight of the goal, in other words focus! In predictive maintenance I see this ageless advice often ignored. Many offerings in this space are tools; legacy technology with an element of predictive analytics added as a “check box”.  It makes a good story:  “Here is a tool that gives you the ability to create your own rules and do your own predictive analytics with a pretty UI.”  Customers get enamored with pretty graphs and slick rules configuration and in doing so lose sight of the goal.  The whole purpose of predictive maintenance is to get your maintenance team at the right location, at the right time, with part in hand before something breaks.  It is all about results – period.

Nobody argues the point above, yet we still see some major companies focusing on the wrong thing when considering predictive analytics for maintenance.  Why?  Maintenance teams are conditioned to find a tool versus finding a solution.

The field of data science grew hand in hand with the explosion of cloud computing.  Cloud computing completely turned the concept of buying hardware and operating systems upside down.  Today cloud based SaaS (software as a service) has eliminated the need for deep expertise in technology and instead simply provides the answer to the business problem.  Now business can buy complete turn key solutions instead of buying a tool, buying the hardware to run the tool, paying their IT department to host the tool and hiring expertise in using and maintaining the tool.

There is a reason data science and machine learning have been the domain of PhD’s and academia – advances are happening at a rapid pace and it takes deep expertise with these tools to get results.  In fact the most important aspect of successful machine learning is the process of feature selection.  It is a rare customer who even understands that a feature is data in context, never mind the hundreds of machine learning algorithms available today.  Yet they believe they should buy a tool that requires them to define their own features and algorithms.  Sadly these same companies relate stories of failed attempts at using data science to solve some problem.  Instead of looking for a solution to a business problem they looked for a tool.  They took their “hand off the plow.”  Savy business leaders understand that buying tools and building expertise in a fast changing technology space that is not the core of their business is not a good use of their resources.  Others understand that business moves too fast and is too competitive to waste time and money buying tools and building expertise when they can buy the complete solution now.  Successful companies know they need a solution not another tool.  They “keep their hand on the plow.”


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