Tuesday, February 23, 2010

What is Intelligence, and why do we need it?

I believe that it is time to get back on topic in this blog, which is Intelligence in manufacturing and manufacturing systems in general. With that in mind I was looking thru my archives and came across something I once wrote as a positioning statement for an intelligence product – I guess it is not hard to figure out what company that was for? So here goes…

In one of my previous posts I tried to bring up the point that we need to consider metrics in the context of what they are needed for and how they are going to be used. I believe that is the best way to understand how to provide the right intelligence in a given scenario. But what is Intelligence? Well that is a very serious subject, but let’s take in the context of manufacturing and process improvement.

Intelligence implies the ability to comprehend; to understand and profit from experience. As such Intelligence is information valued for its timeliness and relevance rather than its detail or accuracy in contrast with "data" which typically refers to precise or particular information, or "fact".

In the context of manufacturing, Intelligence is a fundamental ingredient influencing the system’s level of performance in reaching its objectives. A manufacturing business system (humans included) is a system that learns during its existence. In other words, it learns, for each situation, which response permits it to reach its objectives. It continually acts and by acting reaches its objectives more often than pure chance would indicate. We can observe the following about Intelligence in manufacturing:
Intelligent manufacturing is not a smarter way of producing things; it is a human centric approach where humans interact with the process be it automatic or manual, gathering the right information to take intelligence decisions based on actionable information. It is much more than visibility. Just having the information is of course helpful, but it needs to be taken one step farther. It needs to be provided in a way that people can intuitively capitalize on it using their knowledge and understanding to make effective decisions.
Henri Poincare once noted in a related topic that “Science is facts; just as houses are made of stones, so is science made of facts; but a pile of stones is not a house and a collection of facts is not necessarily science.”
What is an effective decision then? It is a decision that has an outcome that drives increased performance and continuous improvement. Intelligence is therefore not solely about metrics, KPIs or the ability to drill down into the data. In order to increase performance we need to quantify what is important. Hence intelligence is about quantifying what is important, or quantifying the unquantifiable.

Wednesday, February 17, 2010

Why are lay-offs so harmful?

Many thanks to Mark Graban that pointed me to a very interesting News Week article titled “Lay Off the Layoffs - Our over reliance on downsizing is killing workers, the economy - and even the bottom line”, by Dr. Jeffrey Pfeffer. The article speaks to the fact that lay-offs in fact do not save a company money, not in the long run nor in the short term. In fact it may have even more detrimental affects on a company than you may realize. The article states with reference to empirical evidence that
“…contrary to popular belief, companies that announce layoffs do not enjoy higher stock prices than peers—either immediately or over time.”
It is an interesting read for everybody, obviously for them that have been laid-off but also for the people doing the lay offs.

I think that the story behind the story is once again the topic of management and leadership. I strongly believe that in any situation it is always about people. That means that it is the people (managers) and their way of running a company that is the root-cause here. I have said before that you manage processes but you have to lead people. When you just manage people then they become an assets and when hard times are upon us, cutting costs by reducing your capital makes sense – right? Well no – isn’t that obvious - Apparently not?
“In the face of management actions that signal that companies don't value employees, virtually every human-resource consulting firm reports high levels of employee disengagement and distrust of management.”
“Layoffs are more like bloodletting, weakening the entire organism. That's because of the vicious cycle that typically unfolds. A company cuts people. Customer service, innovation, and productivity fall in the face of a smaller and demoralized workforce. The company loses more ground, does more layoffs, and the cycle continues.”
This reminds me of one of Dr. Demmings most commonly used quotes:
"Running a company on visible figures alone is one of the seven deadly diseases of management."
In this case it is financial metrics. It seems that in a recession most management executives are thinking of short term financial metrics rather than the long term health of their company? I am sure that these managers do not intend to do this and that they probably believe that they are doing the right thing. However it is this focus on managing rather than leading that is the problem. Managing the company’s business (The process) is more important than leading the people (organization). The end of the quarter's bottom line is more important than long term viability. Although this seem to be common practice, there is ample proof of companies that thrive by doing differently. Yes, by simply motivating and empowering their people. That is what makes them great companies, and also immensely profitable I may add

We are driven by this need to satisfy investors, whom I may add are also typically about short term gain. It seems that everything revolves around the need to make money now - the typical sales man approach, which is to pick up the closest shiniest pennies rather than to look ahead and possibly see a pot of gold on the horizon. Even if there is not one there at least you looked, and people appreciate that – do not underestimate what that means?

Monday, February 15, 2010

Using metrics and what it tells us about Manufacturing Intelligence

In continuation to some of the other posts in the topic of metrics and KPIs, this time I would like to discuss the use of metrics. So, not so much what the metrics are or which metrics are most important, but how do we use them. If we look at how analysis is performed we may be able to gain some insight into how the data should be collected and structured. This may be for example to support lean or process improvement initiatives. The idea regardless of methodology requires that the team or person gain an understanding of the process and its behaviour based on the data at hand.

I think the best way to frame this up is to tell the story of a persona in a simple scenario. Let’s consider Patrick Process Engineer who is trying to understand yield fluctuations specifically and maybe the yield’s behaviour in general. He is perplexed about why he cannot accurately predict yield given that most of the processes are “in control” (yes, another one of these myths about processes). What he really is striving for is an understanding the process and the best way to investigate it – in other words analyze the process.

Obviously Patrick will be looking at the Yield metric(s) and once he sees some fluctuation he will embark on an analysis. Typically he will perform what I call a high-level analysis, which is kind of a “look-around” in the data and maybe other related metrics to determine patterns. But wait, why patterns. Well whether we like it or not when we analyze processes we naturally look for patterns since that is what complex processes really exhibit. I guess I need to write a bit more about the complex adaptive behavior of manufacturing systems, but let me leave that for a future post. For now let’s just say that the patterns really tell us about the dependencies between the different metrics and parameters in the system.

OK, once Patrick has performed is “high-level” analysis he may then start digging a bit deeper in to some of the areas that may lead him to the root-cause of the fluctuation. He may perform some more detailed analysis, maybe choose to monitor some specific metrics, define some additional more detail or focused metrics. If he really is trying some advanced analysis he may try and observe dependencies between metrics for a period of time. That means monitor maybe a few metrics and how they change in relation to each other.

What is described here is really a simple scenario of human behavior exhibited when we perform troubleshooting. Although this as simple behavior for us, when we think about the data and data structures that we need to support what Patrick is trying to do, we may quickly realize that the complexity abounds. Modern business intelligence concepts such as multidimensional analysis, OLAP, and practices for data aggregation provide the tools. However it takes a lot of work and process knowledge to transform the base process data to such information structures.

This I believe is the main challenge in modern manufacturing systems. Compounding this problem is that effective analysis needs to use information from all the host of system that may reside in a manufacturing business, i.e. ERP, MES, Automation, Historians, LIMS and others. Most manufacturing intelligence tools that are in the market today simply do not address this simple scenario. If we do our inbound marketing work correctly and draw up the scenarios above, with Patrick our main persona, the problem definition is straightforward; however the engineering task required to solve it is not.

Friday, February 12, 2010

What makes a home sell?

This i a bit off topic, but still and interesting question...

What makes a house sell? I have been pondering this question, obviously since I am trying to sell my home. How do you get into the minds of the people that may be potential buyers? There are of course the standard things that the real estate agent tells you to do such as the de-cluttering, remove personal objects, make it clean and tidy, price, the signs, etc. But when you walk into a home what is it that makes one like or dislike this home?

I wish I could get into the minds of these buyers, but as a seller you get no exposure to the real people that visit your home when it is cleaner than it has ever been. They leave no trace, no scent, and no feedback. Maybe I should consider some hidden cameras? Maybe ask them to fill out a questionnaire before they leave – right!

My only method of understanding my potential buyers is by asking others within my network; what is it that made them buy the house they currently own? So this is it, my plea to all - please let me know who my buyer persona is?

Monday, February 8, 2010

When is enough, enough? The art of counting jelly beans.

I was reading an article in National Geographic Blog about counting jelly beans that in a way boiled down what my general belief about metrics (see also another relevant post about metrics). Also, I have lately been involved in MESA’s metrics working group and all of this had me thinking…

The current practice in regards to metrics in operational environments especially in manufacturing is the typical engineering tactic - we need to break down the complexity of the system and figure out what metrics we need. Well one approach is to take a look at what other companies are doing – as in MESA paper we try to figure out if there are any best practices. But is this the right approach for any company or for you? I say no! Metrics are a way to represent patterns in the complex systems that enhance our understanding of its dynamics. We can look at one metric and say we are doing good or bad, which works well if you are a computer since we can take a decision based on this metric. Yet unlike computers, we humans are much better at using our knowledge and understanding to detect patterns and react to them. So if you give us a set of metrics that help us interpret what the system is doing then we do much better. That is exactly what the term "Actionable Intelligence" means.

There are a few important factors that I believe are important:

  • A few metrics used independently are never going to give you the true picture of what is going on.
  • Simply copying what other companies are doing will not work either, since metrics should be driven by what you are trying to achieve – and that changes with time.
  • The Accuracy of the metrics are not necessarily important. What! Yes, I just said it; accuracy is not that important. Let’s think about a jelly bean counting competition, you really don’t needs to know the exact number but be the one that is closest to the precise number, in order to win. Michael Schumacher (if you do not know, he was a 7 time Formula 1 GP winner) once said “… you don’t have to drive your fastest to win, but faster than the guy behind you”.
So why do we obsess about having so much data, detail and precision? Why are we always trying to quantify the unquantifiable, as in 6-Sigma. Maybe it is our upbringing as engineers, that constant quest for details. Really all we need is an indication when things will go wrong and when they are going well? This is of course not to say that sometimes we do have to be very precise as well as accurate, such as in engineering tasks, designs, etc. The art of it all is to know when we are precise enough.

In a blog post Stephen Few states “most poor decisions are caused by lack of understanding, not lack of data”. This is exactly my point, we spend so much time working on detail. For example, how much the ocean water level will rise over the next period of time. Some say a few meters some say 30 meters in the next 100 years. But the point here is that even in a moderate scenario calculation; Venice, New Orleans and the SF Bay Area delta, among other places, will be under water. So if you live there – guess what? You are in trouble, regardless of accuracy.

Friday, February 5, 2010

It has been a while...

It has been a very long while since I have posted anything on this blog. Hopefully this will change – starting right now.

I have just started a new job with NNE Pharmaplan and it looks like a very exciting opportunity. If you did not know NNE Pharmaplan is an engineering consultancy firm focusing on the Life Science industry. The company is quite large and also well known in Europe. With renewed focus on North America I will be responsible for helping Life Science customers with their Manufacturing Systems efforts.

This new opportunity is taking me back to my core expertiseManufacturing Systems (I don’t like to call it MES – Manufacturing Execution Systems because of narrow and misleading perceptions, but more on this in a later post). That being said I still plan to spend time on new media marketing and hopefully help with some new ideas at NNE Pharmaplan.

So watch this space for some interesting discussions and opinions…