Tag Archives: information automation

Excelize Me: 4 Myths & 4 Realities of Racing to Automate

On the eve of our celebration of the American Revolution, here’s a post about another revolution: Industry 4.0.

excelizeITWho remembers VisiCalc, often referred to as the first killer app?  In 1978, this first spreadsheet software ushered in the personal computing boom.  Although it only ran on Apple’s priciest computer (the one with massive 32K RAM), its ability to calculate and recalculate arrays had much to do with the explosion of information automation. By 1985, a next-generation product name Excel conquered the market with significantly more computing capability than its predecessors, eventually adding macros, graphics, nested arrays and easy interface with many other applications.  Today Excel is reportedly in the hands of some 1.3 billion users.  It’s a fascinating tool with more features than almost anyone can use.

But fascination with information automation can be problematical.  In 1996, while TSSC was assisting my company with improvement to machine set-ups, I used Excel to devise an A3 improvement plan complete with graphical VSM current and target states, problems and countermeasures, and milestones and results (documented in a 2012 post, “Value Stream Wrapping.”)   When I proudly showed the document to my teacher, he scoffed “You should spend more time observing, and less time making it pretty.”

I’m reminded of this advice every day during my work with customers.  Why do we feel the need to digitize everything?  From strategic planning to training to project management to idea systems to problem-solving to pull systems, we race to automate, believing that these are improvements.  Here a few myths from Lean implementers, quoted verbatim that I’d like to debunk in honor of my teacher from TSSC:

 

Myth 1:  “We cascade our strategy online to every department creating a line of sight from corporate down to individual department metrics.”
Reality:  Too often this multi-level bill of activities replaces the kind of human discourse needed to effectively communicate and deploy strategy.  An X-type Matrix, for example, nested to multiple levels does not illuminate, it hides connections that would be immediately apparent on a physical strategy deployment wall.

 

Myth 2: “Putting our Idea System online has increased the visibility of ideas.”
Reality:  Online Ideas System software hides ideas.  A factory employee recently referred to her company’s Ideas App as a “black hole.”  Also, when ideas are digitized, the visual nature of a physical idea board is lost to myopia.  We view ideas one at a time rather than components of a system.  And, even though computer literacy of the average employees is improving, the thought of using an app still scares many employees away.

 

Myth 3: “Electronic huddle boards provide real-time standardized information.”
Reality:  Sure, LCD’s are cheap today – maybe even cheaper than a decent whiteboard – but electronic huddle boards suck the life out of creativity and ownership from the front line.   One supervisor complained to me, “It takes me much longer to enter information to the huddle board application than it did to simply write on the whiteboard.  I update it when I can find the time.”   Hardly real-time.

 

Myth 4:  “We are conducting our Lean training online to save time and money.”
Reality:  No doubt, there is an explicit component to Lean learning that may be accomplished sitting a computer screen, and there are slide shares for this, some available through Groupon for peanuts; but real learning only occurs through hands-on practice and coaching.  This is especially true for Lean learning where concepts are counter to conventional thinking.  While the Internet offers an incredible resource for learning, it’s not a substitute for tacit learning — learning by doing.  Organizations that think they are saving time and money by using only online training are actually wasting both.

 

Implicit in all of these myths is the replacement of manual management of information with a machine function – call it the Internet of Things or Industry 4.0, our next industrial revolution.   But what will be the benefits?  Will the killer apps really make industry more flexible and efficient, or will they merely dehumanize the workplace.  What do you think?  Can you cite any other IoT myths?  Please share.

 

Happy 4th.  For iPhone and iPad users only, here’s a fireworks app J

O.L.D.

PS I’m hosting a free “Tea Time with The Toast Dude” webinar and a discussion about Idea Systems, next week after the holiday. Are there gaps that hold you back? Ideas Systems are one of the most powerful and impactful means to engage “everybody everyday” in your improvement process. Yet many fall short of their potential for lack of participation. Join me on Tuesday, July 10 for a “Summer check-up of your idea systems”. What’s working, what can be improved? See you then! Register here.

Artificial Ignorance

For a few years back in tart_inthe early ‘80’s I fell prey to information automation fascination. I managed an IT department transitioning first from a basic accounting system managed by an external service bureau to a batch inventory control system to an order processing and manufacturing control system running on a succession of minicomputers with names like Dec 1170 and HP3000.  If you recognize the names of these systems or if you are familiar with RPG, assembler, Cobol or FORTRAN, then you too may be an old lean dude. The hardware of that decade was slow, flimsy and subject to frequent crashes; the term “user-friendly” as applied to the user interface had not yet been invented.

Today, by comparison, I regularly carry around in my coat pocket a thumb drive with a million times the storage capacity accessible and one thousand times the speed of what was available to my entire company in 1980. And that’s puny compared to the multi-parallel processing power available to businesses today. Today’s super computers pile up so much logged data, that decision rules under the heading of “artificial ignorance” have been created to intentionally ignore data that has been deemed (by someone) to be insignificant. Amazing!

What’s more amazing, however, is that most of the software running on today’s super machines follows essentially the same network-scheduling model we were using in 1980. Call it MRP or ERP, it may be zippier and have more tentacles today than it did then, but the deterministic model that assumes we can know what to produce today based upon a forecast created weeks or months ago is still alive and well. Shigeo Shingo called this model “speculative production.” I call it computerized fortune telling. If production lead times are very long, the fact that we can now run that forecasting model one thousand times faster doesn’t improve its efficacy.

If we add to this model of forecasting and back scheduling a standard cost accounting system whose operating assumptions go back a century, then we have created a model that systematically optimizes local efficiency to four decimal places as it pyramids inventories. Eli Goldratt used to call these calculations “precisely wrong.”

I was at a company several weeks ago that is in the process of replacing a 1980’s MRP system with a later model ERP system. “We’ll be able to allocate our parts for specific orders,” the materials manager, Bob, explained to me. “Hmm,” I thought, “why is that a good thing?”

Bob continued, “We’ll have real-time data.” I reflected, “What does that mean? At best he’ll have a rear view mirror. He’ll be reading yesterday’s news.” Assuming the transactions have been completed correctly and in a timely fashion, Bob will still only know the last place the material has been. Is it still in department A or is it in transit? Or has it arrived in department B, but not yet been transacted? This out of phase situation causes many a supervisor to chase down either parts or transactions to enable production.

“What happened to the pull system you were implementing last year?”, I ask.

“We’ve had to put our continuous improvement activities on hold until we go live,” Bob apologized, “but things will run much smoother once the new system is completely rolled out. We’re discussing an electronic kanban – going paperless.”

And this is where I cringe. I know that it’s been months since the continuous improvement effort was mothballed in order to redeploy resources to the ERP implementation. And I also know that Bob will likely have many more reasons to postpone CI efforts once they do go live. There will be ugly discoveries regarding the differences in rules and assumptions between the new and legacy systems. Material will be over-planned to compensate for shortages arising from start-up misunderstandings. Overtime will be rampant to catch up late deliveries.

Pardon me for sounding cynical. I’ve witnessed it too many times. In the last three months alone, I’ve heard similar stories from nine different organizations large and small. Immense resources are consumed to install hardware and software that runs counter to the objectives of improvement efforts. Thousands of resource hours are spilled into the abyss of information automation with a promise of productivity improvement – hours that would be have been far better spent on simplifying or eliminating questionable business processes. But nobody wants to talk about it publicly. One executive confided recently, “We’ve spent too much money to turn this off now.”

In 1976, Joe Weizenbaum, one of the early leaders in the field of artificial intelligence warned in his landmark book, Computer Power and Human Reason (on Amazon for $.01) that while computers can make decisions based upon rules, only humans should make choices. I worry that with each step change in computer power, human reason takes a step back. Dr. Weizenbaum foresaw the era we now live in where choice is reduced to a set of rules that hide beneath the legitimacy of the “system.” Ironically, this system, built up of nothing more and 0’s and 1’s and once described by Weizenbaum as the “universal machine” because it could be programmed to do anything, has on the contrary become the hugest monument process in any organization. Today’s popular ERP systems, with more than a quarter-billion lines of code, have too often become the tails that wag the dogs.

Maybe I’m just old school, but it seems that thirty-five years after my first love affair with computerization I’m still feeling jilted. How about you? Is your IT strategy supporting productivity and competitiveness or is it the tail that wags the dog? Tell me I’m wrong. Or share a story.

Happy New Year.:)

O.L.D.