Hour by Hour Boards in the Digital World

What does an Hour by Hour board look like in a digital world? This Lean visual management tool that is a common and useful method to drive performance in manufacturing. But what do they look like in the digital paradigm? I find that the go-to is to just digitize them, meaning replicate the whiteboard without much thought about what they can be and how we can impact outcomes, ie drive performance increase. 

If we are to really gain order of magnitude productivity increases when introducing digital technology we have to go past that "just digitize the board" mentality. Let's start by considering why its hour by hour (or some standard period). Its to provide a tangible target to aim performance at with a given frequency. Its also because the operators or person who is supposed to update the board does it at that frequency. 

However if we introduce digital tools then we also introduce means to capture the required data at higher frequencies and also varying frequencies. This can be done a simple screen to quickly quantities, to interactive capture of quantities through buttons, input devices and sensors and ultimately through advanced sensory devices such as vision.  With that in mind it becomes a bit trivial to just do it every hour! In addition we can also capture a lot of context about the data. From the obvious such as operators, stations, orders, etc. but also things like environmental data, events, materials used, stock levels, etc. 

Lets take an example of a digital solution that essentially is capturing good and bad quantities of parts produced with some context such as time stamp, operator, station, shift, product and optionally some comments. However unlike the manual boards the operators can enter data at any given frequency and much more frequent than hour by hour. The system can also prompt and even require that he enter data at a given frequency. This is of course, if we only we rely on manual entries, if we supplement with sensory devices we can get much more granular and frequent data.

Now that we have all this data we can of course display hour by hour board with total quantities. Great but let's think about what else we can derive from this data? First of all we can calculate throughput and output rates, for example:

• Throughputs: Good parts per hour, Good parts per shift, etc.
• Output: Total bad parts by day, total good parts by line

And then include simple predictions of performance, for example:

• Predicted good parts by end of shift, predicted total bad parts by line, etc.

But it doesn't end there! With this data you can also visualize trends of performance for example:

• Trend good parts by line by shift. 
• Daily performance trend 

We can also do comparison by a multitude of dimensions for example:

• Bad parts by vs good parts by operator, or by day 
• Good parts by product for different shifts or operators 

We can take actions on deviations and critical scenarios, for example:

• Send a text when Good parts per hour is below 10

With all this digital data there is just so much insight to gain from just a simple capture of quantities. We now have a continuous feed of information and the hour by hour transforms into a wealth of information and importantly insights. This information can be displayed in numerous, dare I say infinite, formats for use by the operator, supervisor, leadership and any function in the operation. 

And it doesn't end there. With enough volume of data we can start applying more advanced analytics (read AI/ML) and gain insights that we did not uncover. Then operationalize these insights by proactively doing something about the performance predictively and intelligently.

Remember we started by simply capturing good and bad quantities of parts produced in a digital form. This took us from just looking at quantities and performance against a target to the ability to look at performance trends, patterns historically, performance in the context of different dimensions. Then to insights based on human intelligence, taking proactive actions, then to predictive analytics with AI/ML ending with deep insights into our operation. This is where and how digital transformation offers order of magnitude productivity increases.  

Let me end with a favorite quote from Dr. Seuss:

"Think left and think right and think low and think high. Oh, the things you can think up if only you try!"

So do "think high", digital is much more than digitizing, re. the hour by hour board in this example. The "things that you can think" once you have digital data is where the value is.

The Decline of Monoliths and the JAM (Just Another MES) Trap

How many times have we heard this? "We are implements XYZ system and the project plan has a go live date in 1.5 years." We also know that immediately after hearing this statement that anybody with even minimal experience will adds 6 months to this date - just to be realistic. This is what we have been accustomed to in the area of traditional manufacturing systems -there is a sense of inevitability and even desperation. 

Good news, in the current era of digital technology this does not need to be so. As I have explained many times before transformative digital technologies time to value is measured in days and weeks and not years. They are implemented in a bottom up iterative manner that is focused on adding value by making frontline operations more productive. 

But what makes this possible and why can't traditional systems do the same? That is because traditional systems are monolithic, they are built on the premise of providing a business function that works the same for all. The same solution that can serve all industries, in all modalities, in all scenarios, with any equipment, and for all operators. They have to be implemented top-down with a lengthy implementation process that maps out all the requirements, scenarios and contingencies upfront. They require the adaptation of existing operational processes to what the system can support and in the way that it supports it. They provide standardized rigid hierarchical structures for representing manufacturing operations with a standard data model in a one-size fits all approach.  Monolithic systems are also designed for maintainability, meaning that they try to optimize to ease the maintenance and management of the solution by a team with specialized skillsets. 

Bottom Line! Monolithic Solutions rob your organization of rapid time to value and exponential productivity increases that is at the core of the digital transformation (Industry 4.0, Smart Factories, etc).  This may not be news to some but the reason I felt it was necessary to discuss this topic is because I see many companies adopting new digital technologies but then go happily down the path of recreating monoliths. A path that will inevitably result in what I call "Just Another X": JAM, JAL, JAW, JAC - Just Another MES, LIMS, WMS, CMMS, etc. These solutions that will at best be “just as good” as the other MES, LIMS, WMS, CMMS, etc., and will inherently have all the associated shortcomings.

A Composable solution is built from the bottom up in an iterative manner. It is inherently agile and adaptable and provides the most efficient way to digitize manufacturing operations. It provides a solution in which the manufacturing execution is organically integrated with the operations and business processes. It provides the most robust and effective way to increase productivity with a modern digital tools specifically a Frontline Operations Platform.

This is in stark contrast to a Monolithic approach where top down hierarchical process is used to provide a solution that fits within specific constraints that is hard to change. The goal is to fit the solution to the process in contrast to fitting the process to the solution. Composability removes the difficulties associated with adhering to complicated standards and systems. It frees the engineers to focus on rapidly building targeted apps that solve a specific problem, fit the process, and increases the rate of solution development by an order of magnitude.

• Tailored specifically to each process, activity, operation - no compromises.
• Instrumentation of each discrete process - capturing granular data about each activity
• Complexity is distributed across the solution's Apps and easier to maintain
• Highly adaptable and agile - easy to change, minimal impact to overall system behavior

From: "The 5 Trademarks of Agile Organizations"

This brings us back to Holonics and holarchies which explain the fundamental principle enabling agility and why monolithic system will never be able to support agility. We talk all day long about digital transformation but until we understand that the technologies we use have to enable these fundamental principles we will not get the promised order of magnitude productivity increases. Let me close with a quote from what was once the Agility Forum, one of the research initiatives that is the foundation for Industry 4.0: 

“Instead of building something that anticipates a defined range of requirements based on ten or twelve contingencies, build it so it can be deconstructed and reconstructed as needed.” 

                                                                                                   -Rick Dove, Agility Forum