Skip to main content

Magnificent Models | what are you predicting?


The next agenda topic in our executive meeting was IIoT and predictive service. Avid Andy had a feeling that this was going to be a controversial   topic as there was a lot of ambiguity surrounding the definition of data science-based modeling.  This was an opportunity to jump right in and start a brief discussion on the meaning and impact that data science-based learning models could have on the organization.  He began by defining a couple distinct types of models:



  1. The market today is filled with lots of misleading information, our competitors all say they can predict, we ourselves have manufacturers stating that they can also predict, and our customers have an expectation that we are predicting. My question is, predicting what? Aligned to which customer outcome? If we do not have a clear picture of all the elements combined with the customer outcome all we will get are unintelligent responses such as your automobiles "check engine soon" light.
  2. What level of confidence will you need from the predictive model? For instance, let's say that you were trying to predict when the air filters at any given jobsite are going to need to be replaced. Sounds relatively straightforward and the worst thing that would happen is that you may send somebody a bit too early or a bit too late. Another scenario might be when the battery needs to be changed in a pacemaker. The predictive algorithms and the confidence level that you are going to need to have in your outputs will need to be much higher on the replacement of the pacemaker battery.  This all boils down to the level of investment on what your sensing and how you're expected outcome when leveraging that data.



Once you understand the customer's objective (s) you need to combine that with your own business objectives. Is the reason that you are using predictive modeling is to give you an edge in the market? If that is the case than the models that you choose should be single models, possibly only looking at one element and having the right to claim, rightly so, that you are predicting an outcome. However, if you are trying to turn around or mitigate risk within your organization, you may need to look at multiple pieces of equipment and their predictive models to see how, when combined with one another, create different perspectives which may alter your course of business. These are very different approaches, they all need predictive models and data, certainly investment, but their level of sophistication is vastly different. Both are valuable, the bottom line will be how well aligned the model is to your business conditions and environment.



The final thing to remember, don't shy away from collecting data, even the data which you may not see a direct use for today. This data is commonly stored in an inexpensive format often referred to as a data lake. If your ambitions are to mature your predictive models and evolve them eventually into prescriptive models, you will need all the data you can get your hands on.  Andy was beginning to lose his team members in the executive meeting and decided to summarize using a few bullet points;

  • grab as much data as you possibly can
  • leverage other people's models to create a holistic model of your own which can align to customer outcomes
  • start small with laser focus and understand your market and the models value



Learning models, and the algorithms contained within, can drive incredible value to your business. It is key that you understand how the outputs of these data science-based objects influence action with in your current operating environments. Keep in mind that IIoT, data sciences, and even workforce sciences, are as much about the tools as they are about the cultural and market-based changes required to truly evolve your operation.



-----

Next post:  your face is our face

Thoughts?  feel free to leave replies or direct message

See all "last mile worker" posts here:  http://lastmileworkersolutions.com

-----

Comments

Popular posts from this blog

expert at everything...not a problem

Well... I would say sometimes there certainly is a perceived notion that one person is an expert at everything. For the worker "everything" may be defined as the specific area in which you were hired or are constantly scheduled. Our opinions are frequently influenced off of past experience, or information we've received from their coworkers. Unfortunately this only gives us partial insight to that workers expertise and often is limited to their most recent history. Narrowly focused accounting is made of the skills that this individual possess. Come on, can't we figure out a way to leverage all of the skills of a particular worker? One of the challenges has always been that relationship between the activities which need to be accomplished and the myriad skills of individuals within your workforce. In addition, even if you could inventory and get a pretty good handle on the skill sets, they are constantly changing (with any luck) and thus the ineffective process of ...

In$pired

As the steam from Avid Andy's coffee fogged his glasses on this crisp January morning, he reflected on last year and thought enthusiastically about the year ahead.   Sometimes the noise of business is deafening, we rarely take the time to contemplate our moves, instead are often thrown one direction or another.   Hey, face it, if you are reading posts to gain perspective you fall in the group of folks who pride themselves as obsequious hoop-jumpers.   We live to help others and expect that all of those around us feel the same way.   I just love Influential Irene.   Okay, it is out in the open, she is an inspiration for me and so many others.   Irene reminds folks every year, without fail, these three statements which she fondly refers to as "the punchline" (although this is no joke).   Businesses, of any size, will be successful if they remember that it is people that make a company.   Put this advice into practice, today: Sincerity |...

What happened to Customer Service?

Leaving your customer with the sensation that they are highly revered to your organization, isn't that what customer service is all about? However, in order to obtain that level of connection wouldn't it help if every individual which touched the customer sincerely understood what service you are providing? If we go back to my core belief, expressed in other posts, "people want to do the right thing". Taking that at face value, it leaves our primary jobs as mentors and educators. Many complicate this topic by blaming it on the generations, as a matter of fact that is where I was at when I started to think about composing this post. It is true in some ways that over the years our culture in America has changed. You can experience this by visiting different parts of the United States, for instance go to the deep South and you will get a different level of customer service then you may on either of our coasts. Yet that is really a scapegoat to avoid the root pr...