You are currently browsing the category archive for the ‘brain’ category.

Although I have a PLM-twisted brain, I try to read in my free time books and articles that have no direct link with PLM. My main interest goes to people. How do they behave and decide in a society, in a company? What makes them decide to change an existing business?

SapiensI am currently reading the book from Yuval Noah Harari, called Sapiens: A Brief History of Humankind. I still have to finish the book but got intrigued by the following text when he tried to explain why homo sapiens was able to motivate and mobilize larger groups than a tribe:

How did Homo sapiens manage to a critical threshold, eventually founding cities comprising tens of thousands of inhabitants and empires ruling hundreds of millions? The secret was probably the appearance of fiction. Large numbers of strangers can cooperate successfully by believing in common myths.

Here my PLM-twisted brain woke up. What if we could create a  digital PLM myth? Currently, a lot of the PLM arguments are about functions and features, technical capabilities and perceived Return On Investment (ROI). For a digital transformation ROI is hard to estimate as the future state is not known and stable. What if the future state is a myth?  I will think about it when I finish the book and write the myth 🙂

Meanwhile, the rest of this blog post will be a reprint of a post I wrote almost five years ago in a similar context. PLM (old and new) are concepts against our evolution history. Enjoy and discover.

Our brain blocks PLM acceptance (Aug 2012)

tacit_logo.pngThe brain has become popular in the Netherlands in the past two years. Brain scientists have been publishing books sharing their interpretations on various topics of human behavior and the brain.

The common theme of all: The brain is influencing your perceptions, thoughts, and decisions without you even being aware of it.

clip_image005.jpg< added this post: in April 2013 Daniel Kahneman published his book Thinking Fast and Slow I referred in my post from May 2014 to this book – PLM is doomed, unless …>

Some even go that far by claiming certain patterns in the brain can be a proof if you have a certain disorder. It can be for better or for worse.

“It was not me that committed this crime; it was my brain and more…”

Anyway, this post will be full of quotes as I am not the brain expert, still giving the brain an important role (even in PLM)

Our brain blocks PLM acceptance

“My brain? That´s my second favorite organ” – Woody Allen

It is good to be aware of the influence of the brain. I wrote about this several times in the past, when discussing PLM vendor/implementer selection or when even deciding for PLM. Many of my posts are related to the human side of justifying and implementing PLM.

As implementing PLM for me primary is a business change instead of a combination of IT-tools to implement, it might be clear that understanding the inhibitors for PLM change are important to me.

In the PLM communities, we still have a hard job to agree between each other what is the meaning of PLM and where it differs from ERP. See for example this post, and in particular, the comments on LinkedIn (if you are a member of this group): PLM is a business process, not a (software) tool

Moreover, why it is difficult for companies to implement PLM beside ERP (and not as an extension of ERP) – search for PLM and ERP and you find zillions of thoughts and answers (mine too).

Charles_Roxburgh.jpgThe brain plays a major role in the Why PLM we have ERP battle (blame the brain). A week ago I read an older publication from Charles Roxburgh (published in May 2003 by McKinsey) called: Hidden flaws in strategy subtitle: Can insights from behavioral economics explain why good executives back bad strategies.

COULD read, hear and download the full article when you are a registered user. Unfortunate the link has been broken now>

The article has been written long before the financial and global crises were on the agenda and Mr. Roxburgh describes 8 hidden flaws that influence our strategic decision making (and PLM is a strategy).  Note all quotes below are from his publication.

Flaw 1: Overconfidence

We often make decisions with too much confidence and optimism as the brain makes us feel overconfident and overoptimistic about our own capabilities.

Flaw 2: Mental accounting

Avoiding mental accounting traps should be easier if you adhere to a basic rule: that every pound (or dollar or euro) is worth exactly that, whatever the category. In this way, you will make sure that all investments are judged on consistent criteria and be wary of spending that has been reclassified. Be particularly skeptical of any investment labeled “strategic.”

Here I would relate to the difference in IT-spending and budget when you compare ERP and PLM. ERP spending is normal (or strategic) where PLM spending is not understood.

Flaw 3: The status quo bias

People would rather leave things as they are. One explanation for the status quo bias is an aversion to loss—people are more concerned about the risk of loss than they are excited by the prospect of gain.

Another reason why adopting and implementing PLM in an organization is more difficult than for example just automating what we already do.

Flaw 4: Anchoring

Anchoring can be dangerous—particularly when it is a question of becoming anchored to the past

PLM has been anchored with being complex and expensive. Autodesk is trying to change the anchoring. Other PLM-like companies stop talking about PLM due to the anchoring and name what they do differently: 3DExperience, Business Process Automation, …..

Flaw 5: The sunk-cost effect

A familiar problem with investments is called the sunk-cost effect, otherwise known as “throwing good money after bad.” When large projects overrun their schedules and budgets, the original economic case no longer holds, but companies still keep investing to complete them.

I have described several cases in the past anonymously; where companies kept on investing and customizing their ERP environment to achieve PLM goals. Although it never reached the level of acceptance and quality a PLM system could offer, stopping these projects was impossible.

Flaw 6: The herding instinct

This desire to conform to the behavior and opinions of others is a fundamental human trait and an accepted principle of psychology.

Warren Buffett put his finger on this flaw when he wrote, “Failing conventionally is the route to go; as a group, lemmings may have a rotten image, but no individual lemming has ever received bad press.”

A quote in a quote but so true. Innovative thinking, introducing PLM in a company requires a change. Who needs to be convinced? If you do not have consensus (which usually happens as PLM is vague) you battle against the other lemmings.

Flaw 7: Misestimating future hedonistic states

Social scientists have shown that when people undergo major changes in circumstances, their lives typically are neither as bad nor as good as they had expected—another case of how bad we are at estimating. People adjust surprisingly quickly, and their level of pleasure (hedonistic state) ends up, broadly, where it was before

A typical situation every PLM implementation faces: users complaining they cannot work as efficient anymore due to the new system and their work will be a mess if we continue like this. Implementers start to customize quickly, and we are trapped. Let these people ‘suffer’ with the right guidance and motivation for some months (but this is sometimes not the business model the PLM implementer pushes as they need services as income)

Flaw 8: False consensus

People tend to overestimate the extent to which others share their views, beliefs, and experiences—the false-consensus effect. Research shows many causes, including these:

  • confirmation bias, the tendency to seek out opinions and facts that support our own beliefs and hypotheses

  • selective recall, the habit of remembering only facts and experiences that reinforce our assumptions

  • biased evaluation, the quick acceptance of evidence that supports our hypotheses, while contradictory evidence is subjected to rigorous evaluation and almost certain rejection; we often, for example, impute hostile motives to critics or question their competence

  • group-think, the pressure to agree with others in team-based cultures

Although positioned as number 8 by Mr. Roxburgh, I would almost put it on the top when referring to PLM and PLM selection processes. So often a PLM decision has not been made in an objective manner, and PLM selection paths are driven to come to the conclusion we already knew. (Or is this my confirmation bias too )

Conclusion

As scientists describe, and as Mr. Roxburgh describes our strategic thinking is influenced by the brain, and you should be aware of that. PLM is a business strategy and when rethinking your PLM strategy tomorrow, be prepared to avoid these flaws mentioned in this post today.

Advertisements

thinkHappy New Year to all of you and I am wishing you all an understandable and digital future. This year I hope to entertain you again with a mix of future trends related to PLM combined with old PLM basics. This time, one of the topics that are popping up in almost every PLM implementation – numbering schemes – do we use numbers with a meaning, so-called intelligent numbers or can we work with insignificant numbers? And of course, the question what is the impact of changing from meaningful numbers towards unique meaningless numbers.

Why did we create “intelligent” numbers?

IntNumberIntelligent part numbers were used to help engineers and people on the shop floor for two different reasons. As in the early days, the majority of design work was based on mechanical design. Often companies had a one-to-one relation between the part and the drawing. This implied that the part number was identical to the drawing number. An intelligent part number could have the following format: A4-95-BE33K3-007.A

Of course, I invented this part number as the format of an intelligent part number is only known to local experts. In my case, I was thinking about a part that was created in 1995, drawn on A4. Probably a bearing of the 33K3 standard (another intelligent code) and its index is 007 (checked in a numbering book). The version of the drawing (part) is A

A person, who is working in production, assembling the product and reading the BOM, immediately knows which part to use by its number and drawing. Of course the word “immediately” is only valid for people who have experience with using this part. And this was in the previous century not so painful as it is now. Products were not so sophisticated as they are now and variation in products was limited.

Later, when information became digital, intelligent numbers were also used by engineering to classify their parts. The classification digits would assist the engineer to find similar parts in a drawing directory or drawing list.

And if the world had not changed, there would be still intelligent part numbers.

Why no more intelligent part numbers?

There are several reasons why you would not use intelligent part numbers anymore.

  1. PerfectWorldAn intelligent number scheme works in a perfect world where nothing is changing. In real life companies merge with other companies and then the question comes up: Do we introduce a new numbering scheme or is one of the schemes going to be the perfect scheme for the future?If this happened a few times, a company might think: Do we have to through this again and again? As probably topic #2 has also occurred.
  2. The numbering scheme does not support current products and complexity anymore. Products change from mechanical towards systems, containing electronic components and embedded software. The original numbering system has never catered for that. Is there an overreaching numbering standard? It is getting complicated, perhaps we can change ? And here #3 comes in.
  3. BarCodeAs we are now able to store information in a digital manner, we are able to link to this complex part number a few descriptive attributes that help us to identify the component. Here the number is becoming less important, still serving as access to the unique metadata. Consider it as a bar code on a product. Nobody reads the bar code without a device anymore and the device connected to an information system will provide the right information. This brings us to the last point #4.
  4. In a digital enterprise, where data is flowing between systems, we need unique identifiers to connect datasets between systems. The most obvious example is the part master data. Related to a unique ID you will find in the PDM or PLM system the attributes relevant for overall identification (Description, Revision, Status, Classification) and further attributes relevant for engineering (weight, material, volume, dimensions).
    In the ERP system, you will find a dataset with the same ID and master attributes. However here they are extended with attributes related to logistics and finance. The unique identifier provides the guarantee that data is connected in the correct manner and that information can flow or connected between systems without human interpretation or human-spent processing time.

GartnerWorkforceAnd this is one of the big benefits of a digital enterprise, reducing overhead in data handling, often reducing the cost of data handling with 50 % or more (people / customizations)

 

What to do now in your company?

There is no business justification just to start renumbering parts just for future purposes. You need a business reason. Otherwise, it will only increase costs and create a potential for migration errors. Moving to meaningless part numbers can be the best done at the moment a change is required. For example, when you implement a new PLM system or when your company merges with another company. At these moments, part numbering should be considered with the future in mind.

augmentedAnd the future is no longer about memorizing part classifications and numbers, even if you are from the generation that used to structure and manage everything inside your brain. Future businesses rely on digitally connected information, where a person based on machine interpretation of a unique ID will get the relevant and meaningful data. Augmented reality  (picture above) is becoming more and more available. It is now about human beings that need to get ready for a modern future.

 

Conclusion

Intelligent part numbers are a best practice from the previous century. Start to think digital and connected and try to reduce the dependency of understanding the part number in all your business activities. Move towards providing the relevant data for a user. This can be an evolution smoothening a future PLM implementation step.

 

clip_image002Looking forward to discussing this topic and many other PLM related practices with you face to face during the Product Innovation conference in Munich. I will talk about the PLM identity change and lead a focus group session about PLM and ERP integration. Looking from the high-level and working in the real world. The challenge of every PLM implementation.

 

  1. It does not make sense to define the future of PLM
  2. PLM is not an engineering solution anymore
  3. Linearity of business is faster becoming a holdback
  4. The Product in PLM is no longer a mechanical Product
  5. Planet Lifecycle Management has made a next major step

 

It does not make sense to define the future of PLM

future exitAt the beginning of this year, there was an initiative to define the future of PLM for 2025 to give companies, vendors, implementors a guidance to what is critical and needed for PLM in 2015. Have a read here: The future of PLM resides in Brussels.
I believe it is already hard to agree what has been the recognized scope of PLM in the past 10 years, how can we define the future of PLM for the next 10 years. There are several trends currently happening (see the top 5 above) that all can either be in or out of scope for PLM. It is no longer about the definition of PLM; it is dynamically looking towards how businesses adapt their product strategy to new approaches.

Therefore, I am more curious how Product Innovation platforms or Business Innovation platforms will evolve instead of focusing on a definition of what should be PLM in 2025. Have a further look here, such as, The Next Step in PLM’s Evolution: Its Platformization a CIMdata positioning paper.

Conclusion: The future is bright and challenging, let´s not fence it in by definitions.

PLM is not an engineering solution anymore

plmMore and more in all the discussions I had this year with companies looking into PLM, most of them see now PLM as a product information backbone throughout the lifecycle, providing a closed-loop of information flow and visibility across all discipline.

End-to-end visibility, End-to-end tractability, Real-time visibility were some of the buzz-words dropped in many meetings.

These words really express the change happening. PLM is no longer an engineering front-end towards ERP; PLM interacts at each stage of the product lifecycle with other enterprise systems.

End-to-end means when products are manufactured we still follow them through the manufacturing process (serialization) and their behavior in the field (service lifecycle management/field analytics).

All these concepts require companies to align in a horizontal manner, instead of investing in optimizing their silos. Platformization, as discussed above, is a logic step for extending PLM.

Conclusion: If you implement PLM now, start thinking first about the end-to-end flow of information. Or to be more concrete: Don´t be tempted to start with engineering first. It will lock your new PLM again in an extended PDM silo.

 

Linearity of business is faster becoming a holdback

changeTwo years ago I started talking about: Did you notice PLM is changing ? This topic was not in the mainstream of PLM discussions two years ago. Now with the introduction of more and more software in products (products become systems), the linear process of bringing a product to the market has become a holdback.

The market /your customers expect faster and incremental innovations/ upgrades preferably without having to invest again in a new product. If you look back, the linear product development approach has not changed since the Second World War. We automated more and more the linear process. Remember the New Product Introduction hype around 2004 -2006, where companies started to extend the engineering process with a governance process to follow a product´s introduction from its early concept phase toward a globally available product. This process is totally linear. I wrote about it in my post: from a linear world to fast and circular, where the word circular is also addressing the change of delivering products as a service instead of deliver once and scrap them.

One of my favorite presentations is from Chris Armbruster: Rethinking Business for Exponential Times – enjoy if you haven´t seen this one.

Conclusion: The past two years the discussion related to modern, data-driven dynamic products and services has increased rapidly. Now with IoT, it has become a hype to be formalized soon as life goes faster and faster.

 

The Product in Product Lifecycle Management is no longer a mechanical Product

imageI have mentioned it already in the previous point, the traditional way of working, designed and targeting a linear product development process, is no longer enough to support the product lifecycle.

When I started to implement PDM systems in the nineties, we tried to keep electrical engineering outside the scope as we had no clue how to manage their information in the context of a mechanical design. It was very rudimentary. Now PLM best practices exist to collaborate and synchronize around the EBOM in an integrated manner.

The upcoming challenge now is due to the software used in products, which turn them into systems. And not only that, software can be upgraded in a minute. So the classical ECR / ECO processes designed for hardware are creating too much overhead. Agile is the motto for software development processes. Now, we (PLM consultants/vendors) are all working on concepts and implementations where these worlds come together. PLM (Product Lifecycle Management), ALM (Asset Lifecycle Management) and SysLM (System Lifecycle Management as introduced by Prof. Martin Eigner – have a read here) are all abbreviations representing particular domains that need to flow together.

Conclusion: For most companies their products become systems with electronics and software. This requires new management and governance concepts. The challenge for all vendors & implementors.

 

Planet Lifecycle Management has made a next major step

imageFinally good news came in the beginning of December, where for the first time all countries agreed that our planet needs to have a sustainable lifecycle. Instead of the classical lifecycle from cradle to grave we want to apply a sustainable lifecycle to this planet, when it is still possible. This decision is a major breakthrough pushing us all to leave the unsustainable past behind and to innovate and work on the future. The decisions taken in Paris should be considered as a call for innovative thinking. PLM can learn from that as I wrote earlier this year in my post PLM and Global Warming

Conclusion: 2015 was a year where some new trends became clear. Trends will become commodity faster and faster. A challenge for all of us to stay connected and understand what is happening. Never has the human brain challenged before to adapt to change with such an impact.


 

thinkClosing 2015 means for me a week of quietness and stepping out of the fast lane. I wish you all a healthy 2016 with a lot of respect, compromises and changing viewpoints. The current world is too complex to solve issues by one-liners.
Take your time to think and reflect – it works!

SEE AND HEAR YOU BACK IN 2016


Topics discussed in 2014-2015

PLM Basics

PLM and Business Change

From a linear world to a circular and fast-blog

PLM and Business

Conferences

I was sitting outside in the garden during Ascension Day, which is (still) a national holiday in the Netherlands (Thanks God). It was again nice and warm, and it made me think about the parallels between Global warming and PLM.

whyworryClimate change has always been there if we look at the history of our planet. We started to talk about Global Warming when scientist indicated that this time the climate change is caused by human intervention. As a result of vast amounts of carbon dioxide emissions, a greenhouse effect started to become visible. When the first rumors came that global warming began to come up, environmentalists started preaching we have to act NOW before it is too late. Meanwhile at the other side, people began arguing that it was just a coincidence, an opinion.

There is no scientific proof, so why worry?

GlobalWarmingIn the past ten years, the signs and proofs of global warming have become evident and climate conferences filled with people who want to act and on the other side the blockers, try to create progress in the battle against global warming. In particular in Europe governments and companies are starting to become aware that they can contribute to a more sustainable society.

Not enough according to the environmentalists and scientists. As our brains still operate mostly in a prehistoric mode (day-to-day survival, food, home, social status), slow changes and sustainability for next generations are not part of most people concerns. And those people, who make us aware of this lack of priority for sustainability, are considered annoying as they disrupt our lives.

Companies that have invested (heavily) in sustainable business models often have a challenging path to survive against traditional businesses. As the majority of consumers wants cheap. Some examples:

  • Energy: most power plants are heated by burning coal as this is the cheapest option. Shale gas winning became attractive because we need cheap fuel. Alternatives like solar, wind and others cannot compete on price level as long as we do not pay for the damage to nature.
  • Food: produced in bio-farms, where animal wellness or health is not part of the plan. The goal is to deliver xx kilos of meat for the lowest price. Alternative like more natural ways of growing meat or even revolutionary ways (the grown hamburger) cannot compete on price currently unless we are willing to pay for it.
  • The Fashion industry where down in its supply chains human beings are treated like slaves. When you buy a cheap garment, you know somebody has been suffering.

Governments sometimes subsidize or push sustainable technologies as they realize that something has to happen (most of the time for the public opinion – their voters) but there is no consistent strategy as liberals believe every form of support is against open competition. And as long as we let our prehistoric brain run our choices, the earth gets warmer with the consequences being visible more and more.

We know we have to act, but we do not act seriously

Now let´s switch to PLM. The association started when I saw Chad Jackson’s retweet from Lifecycle insights related to top PLM challenges.

2015Challenges

Clearly the message illustrates that costs, time, and technology have priority. Not about what PLM really can establish (even in the context of global warming).

PLM_profPLM started end of the previous century, initially invented by some of the major CAD vendors, Dassault Systemes, PTC, and Siemens. Five years later it was taken more seriously, as also enterprise software vendors, like SAP and Oracle, started to work on their PLM offering. And some years ago even the most skeptic company related to PLM, Autodesk, began to sell a PLM offering.

So like global warming we can conclude: PLM is recognized, and now we can act.

The early adopters of PLM are also in a challenging situation. Their first PLM implementations were very much focused on an IT-infrastructure, allowing data to flow through a global organization, without disrupting the day-to-day business model too much. These implementations are now a burden to many of them: costly and almost impossible to change. Look at the PLM stories from some of the major automotive companies, like Daimler, JLR, PSA, Renault, , Volvo Cars and more.

email_lockThey are all somehow kept hostage by their old implementations (as business continues) however due to changing ownership, business models and technology they cannot benefit from modern PLM concepts as it would be a disruption.

Meanwhile, PLM has evolved from an IT-infrastructure into a business-driven approach to support global, more flexible and customer-driven business processes. Younger companies that are now starting in Asia do not suffer from this legacy and are faster established based on the know-how from the early adopters.

And this is not only happing in the automotive industry. In the recent years, I have seen examples in the Oil & Gas industry, the High-Tech industry (which in theory is relative young) and the Manufacturing industry.

No_roiComing back to the 2015 PLM challenges tweeted by Chad Jackson, it looks like they are related to time and costs. Obviously it is not clear what values PLM can bring to a company outside efficiency gains (ERP/Lean thinking). Modern PLM allows companies to change their business model as I wrote recently: From a linear to fast and circular. No longer is the PLM mission to support companies with product information from cradle to grave but from cradle to cradle. Sustainability and becoming connected to customers are new demands: Operational services instead of selling products, linking it with the need for IoT to understand what is happening.

In the 2015 PLM, the discussion with executives is about purchasing technology instead of the need to change our business for long-term survival. Most investors do not like long-term visions as their prehistoric brains are tuned to be satisfied in the short-term.

changeTherefore, as long as the discussion about PLM is about IT and infrastructure and not about business change, there will be this stall, identical to what happens with addressing global warming. Short term results are expected by the stakeholders, trying to keep up the current model. Strategists and business experts are all talking about the new upcoming digital era, similar to global warming.

We know we have to act, but we do not act seriously

When I posted a short version of this post on LinkedIn on Ascension Day, I got some excellent feedback which I want to share here:

Dieter de Vroomen (independent advisor, interim manager & neighbor) wrote me an email. Dieter does not have a PLM-twisted brain. Therefore I like his opinion:

PLM and Global Warming are both assumptions, mental constructs that we can make plausible with technology and data. Both mindsets save us from disasters through the use of technology. And that’s what both sell. But is that what they produce, what we want? Apple and associates think vice versa, making what first we want and explain later the underlying technology. I miss that with global warming, but certainly PLM. That’s why it sells so bad CxO’s.

I think the point Dieter is making is interesting as he is a non-PLM guy -showing the way CxO might be  thinking. As long as we (PLMers) do not offer a packaged solution, an end-to-end experience, it is hard to convince the C-level. This is one of the significant differences between ERP (its purpose is clearly is tangible) and PLM (see my post PLM at risk! It does not have a clear target).

A more motivating comment came from Ben Muis, consultant and entrepreneur in the fashion industry. We met at the PI Apparel 2013 conference, and I like his passion for bringing innovation to the fashion industry. Read his full comments on my post on LinkedIn as he combined in his career sustainability and PLM. Two quotes from Ben:

As you may know I did quite a bit of work on how the fashion industry could and should be more sustainable in its approach. This was at a time where only a handful of people at best were willing to even think about this. Knowing that in reality the decisions around cost and commercialism were driving the agenda, I drew the conclusion that by improving processes within the industry I could actually cause a sustainability improvement that was driven by commercial desire.

Explaining how you can become involved in the bigger picture and for Ben it is the possibility to keep on working on his passion in a real-time world. And finally:

So there you have it… my reasons for initially thinking your title was very close to the reason I shifted my focus from pure sustainability advice to PLM implementations to begin with. I could drive a real result much quicker. This, as I am sure you will agree, in itself supports the reason for taking PLM seriously

My conclusion:

The topics PLM and Global Warming have a lot in common. The awareness exists. However when it comes to action, we are blocked by our prehistoric brain, thinking about short term benefits. This will not change in the next 1000 years. Therefore, we need organizations and individuals that against all odds take the steep path and have a vision of change, breaking the old models and silos. It will cost money, it will require a sacrifice and the reward will only be noticed by next generations. What a shame

A final quote before going back to standard PLM matter in upcoming posts:

“Everything is theoretically impossible, until it is done.”

Robert A. Heinlein

Mindmap image courtesy of www.mindmapart.comJane Genovese

NoChangeHuman beings are a strange kind of creatures. We think we make a decision based on logic, and we think we act based on logic. In reality, however, we do not like to change, if it does not feel good, and we are lazy in changing our habits.

Disclaimer: It is a generalization which is valid for 99 % of the population. So if you feel offended by the previous statement, be happy as you are one of the happy few.

Our inability to change can be seen in the economy (only the happy few share). We see it in relation to global climate change. We see it in territorial fights all around the world.

Owning instead of sharing.  ?

The cartoon below gives an interesting insight how personal interests are perceived more important than general interest.

clip_image001

It is our brain !

More and more I realize that the success of PLM is also related to his human behavior; we like to own and find it difficult to share. PLM primarily is about sharing data through all stages of the lifecycle. A valid point why sharing is rare , is that current PLM systems and their infrastructures are still too complex to deliver shared information with ease. However, the potential benefits are clear when a company is able to transform its business into a sharing model and therefore react and anticipate much faster on the outside world.

But sharing is not in our genes, as:

  • In current business knowledge is power. Companies fight for their IP; individuals fight for their job security by keeping some specific IP to themselves.
  • As a biological organism, composed of a collection of cells, we are focused on survival of our genes. Own body/family first is our biological message.

Breaking these habits is difficult, and I will give some examples that I noticed the past few weeks. Of course, it is not completely a surprise for readers of my blog, as a large number of my recent posts are related to the complexity of change. Some are related to human behavior:

August 2012: Our brain blocks PLM acceptance
April 2014: PLM and Blockers

Ed Lopategui, an interesting PLM blogger, see http://eng-eng.com, wrote a long comment to my PLM and Blockers post. The (long) quote below is exactly describing what makes PLM difficult to implement within a company full of blockers :

“I also know that I was focused on doing the right thing – even if cost me my position; and there were many blockers who plotted exactly that. I wore that determination as a sort of self-imposed diplomatic immunity and would use it to protect my team and concentrate any wrath on just myself. My partner in that venture, the chief IT architect admitted on several occasions that we wouldn’t have been successful if I had actually cared what happened to my position – since I had to throw myself and the project in front of so many trains. I owe him for believing in me.

But there was a balance. I could not allow myself to reach a point of arrogance; I would reserve enough empathy for the blockers to listen at just the right moments, and win them over. I spent more time in the trenches than most would reasonably allow. It was a ridiculously hard thing and was not without an intellectual and emotional cost.

In that crucible, I realized that finding people with such perspective (putting the ideal above their own position) within each corporation is *exceptionally* rare. People naturally don’t like to jump in front of trains. It can be career-limiting. That’s kind of a problem, don’t you think? It’s a limiting factor without a doubt, and not one that can be fulfilled with consultants alone. You often need someone with internal street cred and long-earned reputation to push through the tough parts”

Ed concludes that it is exceptionally rare to find people putting the ideal above their own position. Again referring to the opening statement that only a (happy) few are advocates for change

Now let´s look at some facts why it is exceptionally rare, so we feel less guilty.

On Intelligence

clip_image003Last month I read the book On Intelligence from Jeff Hawkins well written by Sandra Blakeslee. (Thanks Joost Schut from KE-Works for pointing me to this book).

Although it was not the easiest book to read during a holiday, it was well written considering the complexity of the topic discussed. Jeff describes how the information architecture of the brain could work based on the neocortex layering.

In his model, he describes how the brain processes information from our senses, first in a specific manner but then more and more in an invariant approach. You have to read the book to get the full meaning of this model. The eye opener for me was that Jeff described the brain as a prediction engine. All the time the brain anticipates what is going to happen, based on years of learning. That’s why we need to learn and practice building and enrich this information model.

And the more and more specialized you are on a particular topic, it can be knowledge but it can also be motoric skill, the deeper in the neocortex this pattern is anchored. This makes is hard to change (bad) practices.

The book goes much further, and I was reading it more in the context of how artificial intelligence or brain-like intelligence could support the boring PLM activities. I got nice insights from it, However the main side observation was; it is hard to change our patterns. So if you are not aware of it, your subconscious will always find reasons to reject a change. Follow the predictions !

Thinking Fast and Slow

clip_image005And this is exactly the connection with another book I have read before: Thinking Fast and Slow from Daniel Kahneman. Daniel explains that our brain is running its activities on two systems:

System 1: makes fast and automatic decisions based on stereotypes and emotions. System 1 is what we are using most of the time, running often in subconscious mode. It does not cost us much energy to run in this mode.

System 2: takes more energy and time; therefore, it is slow and pushes us to be conscious and alert. Still system 2 can be influenced by various external, subconscious factors.

Thinking Fast and Slow nicely complements On Intelligence, where system 1 described by Daniel Kahneman is similar to the system Jeff Hawkins describes as the prediction engine. It runs in an subconscious mode, with optimal energy consumption allowing us to survive most of the time.

Fast thinking leads to boiling frogs

clip_image007And this links again to the boiling frog syndrome. If you are not familiar with the term follow the link. In general it means that people (and businesses) are not reacting on (life threating) outside change when it goes slowly, but would react immediately if they are confronted with the end result. (no more business / no more competitive situation)

Conclusion: our brain by default wants to keep business in predictive mode, so implementing a business change is challenging, as all changes are painful and against our subconscious system.

So PLM is doomed, unless we change our brain behavior ?

The fact that we are not living in caves anymore illustrates that there have been always those happy few that took a risk and a next step into the future by questioning and changing comfortable habits. Daniel Kahneman´s system 2 and also Jeff Hawkins talk about the energy it takes to change habits, to learn new predictive mechanisms. But it can be done.

I see two major trends that will force the classical PLM to change:

  • The amount of connected data becomes so huge, it does not make sense anymore to store it and structure the information in a single system. The time required to structure data does not deliver enough ROI in a fast moving society. The old “single system that stores all”-concept is dying.
  • The newer generations (generation Y and beyond) grew up with the notion that it is impossible to learn, capture and own specific information. They developed different skills to interpret data available from various sources, not necessary own and manage it all.

These two trends lead to the point where it becomes clear that the future in system thinking becomes obsolete. It will be about connectivity and interpretation of connected data, used by apps, running on a platform. The openness of the platform towards other platform is crucial and will be the weakest link.

Conclusion:

The PLM vision is not doomed and with a new generations of knowledge workers the “brain change” has started. The challenge is to implement the vision across systems and silos in an organization. For that we need to be aware that it can be done and allocate the “happy few” in your company to enable it.

 

image

What do you think  ???????????????????????????

%d bloggers like this: