You are currently browsing the tag archive for the ‘Business Change’ tag.

This post is a rewrite of an article I wrote on LinkedIn two years ago and modified it to my current understanding. When you are following my blog, in particular, the posts related to the business change needed to transform a company towards a data-driven digital enterprise, one of the characteristics of digital is about the real-time availability of information. This has an impact on everyone working in such an organization. My conversations are in the context of PLM (Product Lifecycle Management) however I assume my observations are valid for other domains too.

Real-time visibility is going to be the big differentiator for future businesses, and in particular, in the PLM domain, this requires a change from document-centric processes towards data-driven processes.

Documents have a lot of disadvantages.  Documents lock information in a particular format and document handling results in sequential processes, where one person/one discipline at the time is modifying or adding content. I described the potential change in my blog post: From a linear world to fast and circular?

From a linear world to fast and circular

In that post, I described that a more agile and iterative approach to bring products and new enhancements to the market should have an impact on current organizations. A linear organization, where products are pushed to the market, from concept to delivery, is based on working in silos and will be too slow to compete against future, modern digital enterprises. This because departmental structures with their own hierarchy block fast moving of information, and often these silos perform filtering/deformation of the information.  It becomes hard to have a single version of the truth as every department, and its management will push for their measured truth.

A matching business model related to the digital enterprise is a matrix business model, where multi-disciplinary teams work together to achieve their mission. An approach that is known in the software industry, where parallel and iterative work is crucial to continuous deliver incremental benefits.

Image:  21stcenturypublicservant.wordpress.com/

In a few of my projects, I discovered this correlation with software methodology that I wanted to share. One of my clients was in the middle of moving from a document-centric approach toward a digital information backbone, connecting the RFQ phase and conceptual BOM through design, manufacturing definition, and production. The target was to have end-to-end data continuity as much as possible, meanwhile connecting the quality and project tasks combined with issues to this backbone.

The result was that each individual had a direct view of their current activities, which could be a significant quantity for some people engaged in multiple projects.  Just being able to measure these numbers already lead to more insight into an individual’s workload. At the time we discussed with the implementation team the conceptual dashboard for an individual, it lead to questions like: “Can the PLM system escalate tasks and issues to the relevant manager when needed?” and  “Can this escalation be done automatically? “

And here we started the discussion. “Why do you want to escalate to a manager?”  Escalation will only give more disruption and stress for the persons involved. Isn´t the person qualified enough to make a decision what is important?

One of the conclusions of the discussion was that currently, due to lack of visibility of what needs to be done and when and with which urgency, people accept things get overlooked. So the burning issues get most of the attention and the manager’s role is to make things burning to get it done.

When discussing further, it was clear that thanks to the visibility of data, real critical issues will appear at the top of an individual’s dashboard. The relevant person can immediately overlook what can be achieved and if not, take action. Of course, there is the opportunity to work on the easy tasks only and to ignore the tough ones (human behavior) however the dashboard reveals everything that needs to be done – visibility. Therefore if a person learns to manage their priorities, there is no need for a manager to push anymore, saving time and stress.

The ultimate conclusion of our discussion was: Implementing a modern PLM environment brings first of all almost 100 % visibility, the single version of the truth. This new capability breaks down silos, a department cannot hide activities behind their departmental wall anymore. Digital PLM allows horizontal multidisciplinary collaboration without the need going through the management hierarchy.

It would mean Power to People, in case they are stimulated to do so. And this was the message to the management: “ you have to change too, empower your people.”

What do you think – will this happen? This was my question in 2015.  Now two years later I can say some companies have seen the potential of the future and are changing their culture to empower their employees working in multidisciplinary teams. Other companies, most of the time with a long history in business, are keeping their organizational structure with levels of middle management and maintain a culture that consolidates the past.

Conclusion

A digital enterprise empowers individuals allowing companies to become more proactive and agile instead of working within optimized silos. In silos, it appears that middle management does not trust individuals to prioritize their work.  The culture of a company and its ability to change are crucial for the empowerment of individuals The last two years there is progress in understanding the value of empowered multidisciplinary teams.

Is your company already empowering people ? Let us know !

Note: After speaking with Simon, one of my readers who always gives feedback from reality, we agreed that multidisciplinary teams are very helpful for organizations. However you will still need a layer of strategic people securing standard ways of working and future ways of working as the project teams might be to busy doing their job. We agreed this is the role for modern middle management.
DO YOU AGREE ?

Advertisements

Last week I posted my first review of the PDT Europe conference. You can read the details here: The weekend after PDT Europe (part 1).  There were some questions related to the abbreviation PDT. Understanding the history of PDT, you will discover it stands for Product Data Technology. Yes, there are many TLA’s in this world.

Microsoft’s view on the digital twin

Now back to the conference. Day 2 started with a remote session from Simon Floyd. Simon is Microsoft’s Managing Director for Manufacturing Industry Architecture Enterprise Services and a frequent speaker at PDT. Simon shared with us Microsoft’s viewpoint of a Digital Twin, the strategy to implement a Digit Twin, the maturity status of several of their reference customers and areas these companies are focusing. From these customers it was clear most companies focused on retrieving data in relation to maintenance, providing analytics and historical data. Futuristic scenarios like using the digital twin for augmented reality or design validation. As I discussed in the earlier post, this relates to my observations, where creating a digital thread between products in operations is considered as a quick win. Establishing an end-to-end relationship between products in operation and their design requires many steps to fix. Read my post: Why PLM is the forgotten domain in digital transformation.

When discussing the digital twin architecture, Simon made a particular point for standards required to connect the results of products in the field. Connecting a digital twin in a vendor-specific framework will create a legacy, vendor lock-in, and less open environment to use digital twins. A point that I also raised in my presentation later that day.

Simon concluded with a great example of potential future Artificial Intelligence, where an asset based on its measurements predicts to have a failure before the scheduled maintenance stop and therefore requests to run with a lower performance so it can reach the maintenance stop without disruption.

Closing the lifecycle loop

Sustainability and the circular economy has been a theme at PDT for some years now too. In his keynote speech, Torbjörn Holm from Eurostep took us through the global megatrends (Hay group 2030) and the technology trends (Gartner 2018) and mapped out that technology would be a good enabler to discuss several of the global trends.

Next Torbjörn took us through the reasons and possibilities (methodologies and tools) for product lifecycle circularity developed through the ResCoM project in which Eurostep participated.

The ResCoM project (Resource Conservative Manufacturing) was a project co-funded by the European Commission and recently concluded. More info at www.rescom.eu

Torbjörn concluded discussing the necessary framework for Digital Twin and Digital Thread(s), which should be based on a Model-Based Definition, where ISO 10303 is the best candidate.

Later in the afternoon, there were three sessions in a separate track, related to design optimization for value, circular and re-used followed by a panel discussion. Unfortunate I participated in another track, so I have to digest the provided materials still. Speakers in that track were Ola Isaksson (Chalmers University), Ingrid de Pauw & Bram van der Grinten (IDEAL&CO) and Michael Lieder (KTH Sweden)

Connecting many stakeholders

Rebecca Ihrfors, CIO from the Swedish Defense Material Administration (FMV) shared her plans on transforming the IT landscape to harmonize the current existing environments and to become a broker between industry and the armed forces (FM). As now many of the assets come with their own data sets and PDM/PLM environments, the overhead to keep up all these proprietary environments is too expensive and fragmented. FWM wants to harmonize the data they retrieve from industry and the way they offer it to the armed forces in a secure way. There is a need for standards and interoperability.

The positive point from this presentation was that several companies in the audience and delivering products to Swedish Defense could start to share and adapt their viewpoints how they could contribute.

Later in the afternoon, there were three sessions in a separate track rented to standards for MBE inter-operability and openness that would fit very well in this context. Brian King (Koneksys), Adrian Murton (Airbus UK) and Magnus Färneland (Eurostep) provided various inputs, and as I did not attend these parallel sessions I will dive deeper in their presentations at a later time

PLM something has to change – bimodal and more

In my presentation, which you can download from SlideShare here: PLM – something has to change. My main points were related to the fact that apparently, companies seem to understand that something needs to happen to benefit really from a digital enterprise. The rigidness from large enterprise and their inhibitors to transform are more related to human and incompatibility issues with the future.

How to deal with this incompatibility was also the theme for Martin Eigner’s presentation (System Lifecycle Management as a bimodal IT approach) and Marc Halpern’s closing presentation (Navigating the Journey to Next Generation PLM).

Martin Eigner’s consistent story was about creating an extra layer on top of the existing (Mode 1) systems and infrastructure, which he illustrated by a concept developed based on Aras.

By providing a new digital layer on top of the existing enterprise, companies can start evolving to a modern environment, where, in the long-term, old Mode 1 systems will be replaced by new digital platforms (Mode 2). Oleg Shilovitsky wrote an excellent summary of this approach. Read it here: Aras PLM  platform “overlay” strategy explained.

Marc Halpern closed the conference describing his view on how companies could navigate to the Next Generation PLM by explaining in more detail what the Gartner bimodal approach implies. Marc’s story was woven around four principles.

Principle 1 The bimodal strategy as the image shows.

Principle 2 was about Mode 1 thinking in an evolutionary model. Every company has to go through maturity states in their organization, starting from ad-hoc, departmental, enterprise-based to harmonizing and fully digital integrated. These maturity steps also have to be taken into account when planning future steps.

Principle 3 was about organizational change management, a topic often neglected or underestimated by product vendors or service providers as it relates to a company culture, not easy to change and navigate in a particular direction.

Finally, Principle 4 was about Mode 2 activities. Here an organization should pilot (in a separate environment), certify (make sure it is a realistic future), adopt (integrate it in your business) and scale (enable this new approach to exists and grow for the future).

Conclusions

This post concludes my overview of PDT Europe 2017. Looking back there was a quiet aligned view of where we are all heading with PLM and related topics. There is the hype an there is reality, and I believe this conference was about reality, giving good feedback to all the attendees what is really happening and understood in the field. And of course, there is the human factor, which is hard to influence.

Share your experiences and best practices related to moving to the next generation of PLM (digital PLM ?) !

 

 

 

PDT Europe is over, and it was this year a surprising aligned conference, showing that ideas and concepts align more and more for modern PLM. Håkan Kårdén opened the conference mentioning the event was fully booked, about 160 attendees from over 19 countries. With a typical attendance of approx. 120 participants, this showed the theme of the conference: Continuous Transformation of PLM to support the Lifecycle Model-Based Enterprise was very attractive and real. You can find a history of tweets following the hashtag #pdte17

Setting the scene

Peter Bilello from CIMdata kicked-off by bringing some structure related to the various Model-Based areas and Digital Thread. Peter started by mentioning that technology is the least important issue as organization culture, changing processing and adapting people skills are more critical factors for a successful adoption of modern PLM. Something that would repeatedly be confirmed by other speakers during the conference.

Peter presented a nice slide bringing the Model-Based terminology together on one page. Next, Peter took us through various digital threads in the different stages of the product lifecycle. Peter concluded with the message that we are still in a learning process redefining optimal processes for PLM, using Model-Based approaches and Digital Threads and thanks (or due) to digitalization these changes will be rapid. Ending with an overall conclusion that we should keep in mind:


It isn’t about what we call digitalization; It is about delivering value to customers and all other stakeholders of the enterprise

Next Marc Halpern busted the Myth of Digital Twins (according to his session title) and looked into realistic planning them. I am not sure if Marc smashed some of the myths although it is sure Digital Twin is at the top of the hype cycle and we are all starting to look for practical implementations. A digital twin can have many appearances and depends on its usage. For sure it is not just a 3D Virtual model.

There are still many areas to consider when implementing a digital twin for your products. Depending on what and how you apply the connection between the virtual and the physical model, you have to consider where your vendor really is in maturity and avoid lock in on his approach. In particular, in these early stages, you are not sure which technology will last longer, and data ownership and confidentially will play an important role. And opposite to quick wins make sure your digital twin is open and use as much as possible open standards to stay open for the future, which also means keep aiming for working with multiple vendors.

Industry sessions

Next, we had industry-focused sessions related to a lifecycle Model-Based enterprise and later in the afternoon a session from Outotec with the title: Managing Installed Base to Unlock Service opportunities.

The first presentation from Väino Tarandi, professor in IT in Construction at KTH Sweden presented his findings related to BIM and GIS in the context of the lifecycle, a test bed where PLCS meets IFC. Interesting as I have been involved in BIM Level 3 discussions in the UK, which was already an operational challenge for stakeholders in the construction industry now extended with the concept of the lifecycle. So far these projects are at the academic level, and I am still waiting for companies to push and discover the full benefits of an integrated approach.

Concepts for the industrial approach could be learned from Outotec as you might understand later in this post. Of course the difference is that Outotec is aiming for data ownership along the lifecycle, where in case of the construction industries, each silo often is handled by a different contractor.

Fredrik Ekström from Swedish Transport Administration shared his challenges of managing assets for both road and railway transport – see image on the left. I have worked around this domain in the Netherlands, where asset management for infrastructure and asset management for the rail infrastructure are managed in two different organizations. I believe Fredrik (and similar organizations) could learn from the concepts in other industries. Again Outotec’s example is also about having relevant information to increase service capabilities, where the Swedish Transport Administration is aiming to have the right data for their services. When you look at the challenges reported by Fredrik, I assume he can find the answers in other industry concepts.

Outotec’s presentation related to managing installed base and unlock service opportunities explained by Sami Grönstrand and Helena Guiterrez was besides entertaining easy to digest content and well-paced. Without being academic, they explained somehow the challenges of a company with existing systems in place moving towards concepts of a digital twin and the related data management and quality issues. Their practical example illustrated that if you have a clear target, understanding better a customer specific environment to sell better services, can be achieved by rational thinking and doing, a typical Finish approach. This all including the “bi-modal approach” and people change management.

Future Automotive

Ivar Hammarstadt, Senior Analyst Technology Intelligence for Volvo Cars Corporation entertained us with a projection toward the future based on 160 years of automotive industry. Interesting as electrical did not seem to be the only way to go for a sustainable future depending on operational performance demands.

 

Next Jeanette Nilsson and Daniel Adin from Volvo Group Truck shared their findings related to an evaluation project for more than one year where they evaluated the major PLM Vendors (Dassault Systemes / PTC / Siemens) on their Out-of-the-box capabilities related to 3D product documentation and manufacturing.

They concluded that none of the vendors were able to support the full Volvo Truck complexity in a OOTB matter. Also, it was a good awareness project for Volvo Trucks organization to understand that a common system for 3D geometry reduces the need for data transfers and manual data validation. Cross-functional iterations can start earlier, and more iterations can be performed. This will support a shortening of lead time and improve product quality. Personally, I believe this was a rather expensive approach to create awareness for such a conclusion, pushing PLM vendors in a competitive pre-sales position for so much detail.

Future Aerospace

Kenny Swope from Boeing talked us through the potential Boeing journey towards a Model-Based Enterprise. Boeing has always been challenging themselves and their partners to deliver environments close to what is possible. Look at the Boeing journey and you can see that already in 2005 they were aiming for an approach that most of current manufacturing enterprises cannot meet. And now they are planning their future state.

To approach the future state Boeing aims to align their business with a single architecture for all aspects of the company. Starting with collecting capabilities (over 400 in 6 levels) and defining value streams (strategic/operational) the next step is mapping the capabilities to the value streams.  Part of the process would be to look at the components of a value stream if they could be fulfilled by a service. In this way you design your business for a service-oriented architecture, still independent from any system constraints. As Kenny states the aerospace and defense industry has a long history and therefore slow to change as its culture is rooted in the organization. It will be interesting to learn from Kenny next hear how much (mandatory) progress towards a model-based enterprise has been achieved and which values have been confirmed.

Gearing up for day 2

Martin Eigner took us in high-speed mode through his vision and experience working in a bi-modular approach with Aras to support legacy environments and a modern federated layer to support the complexity of a digital enterprise where the system architecture is leading. I will share more details on these concepts in my next post as during day 2 of PDT Europe both Marc Halpern and me were talking related to this topic, and I will combine it in a more extended story.

The last formal presentation for day one was from Nigel Shaw from Eurostep Ltd where he took us through the journey of challenges for a model-based enterprise. As there will not be a single model that defines all, it will be clear various models and derived models will exist for a product/system.  Interesting was Nigel’s slide showing the multiple models disciplines can have from an airplane (1948). Similar to the famous “swing” cartoon, used to illustrate that every single view can be entirely different from the purpose of the product.

Next are these models consistent and still describing the same initial specified system. On top of that, even the usage of various modeling techniques and tools will lead to differences in the system. And the last challenge on top is managing the change over the system’s lifecycle. From here Nigel stepped into the need for digital threads to govern relations between the various views per discipline and lifecycle stage, not only for the physical and the virtual twin.  When comparing the needs of a model-based enterprise through its lifecycle, Nigel concluded that using PLCS as a framework provides an excellent fit to manage such complexity.

Finally, after a panel discussion, which was more a collection of opinions as the target was not necessary to align in such a short time, it was time for the PDT dinner always an excellent way to share thoughts and verify them with your peers.

Conclusion

Day 1 was over before you knew it without any moment of boredom and so I hope is also this post. Next week I will close reviewing the PDT conference with some more details about my favorite topics.

 

As I am preparing my presentation for the upcoming PDT Europe 2017 conference in Gothenburg, I was reading relevant experiences to a data-driven approach. During PDT Europe conference we will share and discuss the continuous transformation of PLM to support the Lifecycle Model-Based Enterprise. 

One of the direct benefits is that a model-based enterprise allows information to be shared without the need to have documents to be converted to a particular format, therefore saving costs for resources and bringing unprecedented speed for information availability, like what we are used having in a modern digital society.

For me, a modern digital enterprise relies on data coming from different platforms/systems and the data needs to be managed in such a manner that it can serve as a foundation for any type of app based on federated data.

This statement implies some constraints. It means that data coming from various platforms or systems must be accessible through APIs / Microservices or interfaces in an almost real-time manner. See my post Microservices, APIs, Platforms and PLM Services. Also, the data needs to be reliable and understandable for machine interpretation. Understandable data can lead to insights and predictive analysis. Reliable and understandable data allows algorithms to execute on the data.

Classical ECO/ECR processes can become highly automated when the data is reliable, and the company’s strategy is captured in rules. In a data-driven environment, there will be much more granular data that requires some kind of approval status. We cannot do this manually anymore as it would kill the company, too expensive and too slow. Therefore, the need for algorithms.

What is understandable data?

I tried to avoid as long as possible academic language, but now we have to be more precise as we enter the domain of master data management. I was triggered by this recent post from Gartner: Gartner Reveals the 2017 Hype Cycle for Data Management. There are many topics in the hype cycle, and it was interesting to see Master Data Management is starting to be taken seriously after going through inflated expectations and disillusionment.

This was interesting as two years ago we had a one-day workshop preceding PDT Europe 2015, focusing on Master Data Management in the context of PLM. The attendees at that workshop coming from various companies agreed that there was no real MDM for the engineering/manufacturing side of the business. MDM was more or less hijacked by SAP and other ERP-driven organizations.

Looking back, it is clear to me why in the PLM space MDM was not a real topic at that time. We were still too much focusing and are again too much focusing on information stored in files and documents. The only area touched by MDM was the BOM, and Part definitions as these objects also touch the ERP- and After Sales-  domain.

Actually, there are various MDM concepts, and I found an excellent presentation from Christopher Bradley explaining the different architectures on SlideShare: How to identify the correct Master Data subject areas & tooling for your MDM initiative. In particular, I liked the slide below as it comes close to my experience in the process industry

Here we see two MDM architectures, the one of the left driven from ERP. The one on the right could be based on the ISO-15926 standard as the process industry has worked for over 25 years to define a global exchange standard and data dictionary. The process industry was able to reach such a maturity level due to the need to support assets for many years across the lifecycle and the relatively stable environment. Other sectors are less standardized or so much depending on new concepts that it would be hard to have an industry-specific master.

PLM as an Application Specific Master?

If you would currently start with an MDM initiative in your company and look for providers of MDM solution, you will discover that their values are based on technology capabilities, bringing data together from different enterprise systems in a way the customer thinks it should be organized. More a toolkit approach instead of an industry approach. And in cases, there is an industry approach it is sporadic that this approach is related to manufacturing companies. Remember my observation from 2015: manufacturing companies do not have MDM activities related to engineering/manufacturing because it is too complicated, too diverse, too many documents instead of data.

Now with modern digital PLM, there is a need for MDM to support the full digital enterprise. Therefore, when you combine the previous observations with a recent post on Engineering.com from Tom Gill: PLM Initiatives Take On Master Data Transformation I started to come to a new hypotheses:

For companies with a model-based approach that has no MDM in place, the implementation of their Product Innovation Platform (modern PLM) should be based on the industry-specific data definition for this industry.

Tom Gill explains in his post the business benefits and values of using the PLM as the source for an MDM approach. In particular, in modern PLM environments, the PLM data model is not only based on the BOM.  PLM now encompasses the full lifecycle of a product instead of initially more an engineering view. Modern PLM systems, or as CIMdata calls them Product Innovation Platforms, manage a complex data model, based on a model-driven approach. These entities are used across the whole lifecycle and therefore could be the best start for an industry-specific MDM approach. Now only the industries have to follow….

Once data is able to flow, there will be another discussion: Who is responsible for which attributes. Bjørn Fidjeland from plmPartner recently wrote: Who owns what data when …?  The content of his post is relevant, I only would change the title: Who is responsible for what data when as I believe in a modern digital enterprise there is no ownership anymore – it is about sharing and responsibilities

 

Conclusion

Where MDM in the past did not really focus on engineering data due to the classical document-driven approach, now in modern PLM implementations, the Master Data Model might be based on the industry-specific data elements, managed and controlled coming from the PLM data model

 

Do you follow my thoughts / agree ?

 

 

Last week I published a dialogue I had with Flip van der Linden, a fellow Dutchman and millennial, eager to get a grip on current PLM. You can read the initial post here: A PLM dialogue.  In the comments, Flip continued the discussion (look here).  I will elaborate om some parts of his comments and hope some others will chime in. It made me realize that in the early days of blogging and LinkedIn, there were a lot of discussions in the comments. Now it seems we become more and more consumers or senders of information, instead of having a dialogue. Do you agree? Let me know.

Point 1

(Flip) PLM is changing – where lies the new effort for (a new generation of) PLM experts.  I believe a huge effort for PLM is successful change management towards ‘business Agility.’ Since a proper response to an ECR/ECO would evidently require design changes impacting manufacturing and even after-sales and/or legal.  And that’s just the tip of the iceberg.

 

You are right, the main challenge for future PLM experts is to explain and support more agile processes, mainly because software has become a major part of the solution. The classical, linear product delivery approach does not match the agile, iterative approach for software deliveries. The ECR/ECO process has been established to control hardware changes, in particular because there was a big impact on the costs. Software changes are extremely cheap and possible fast, leading to different change procedures. The future of PLM is about managing these two layers (hardware/software) together in an agile way. The solution for this approach is that people have to work in multi-disciplinary teams with direct (social) collaboration and to be efficient this collaboration should be done in a digital way.

A good article to read in this context is Peter Bilello’s article: Digitalisation enabled by product lifecycle management.

 

(Flip) What seems to be missing is an ‘Archetype’ of the ideal transformed organization. Where do PLM experts want to go with these businesses in practice? Personally, I imagine a business where DevOps is the standard, unique products have generic meta-data, personal growth is an embedded business process and supply chain related risks are anticipated on and mitigated through automated analytics. Do you know of such an evolved archetypal enterprise model?

I believe the ideal archetype does not exist yet. We are all learning, and we see examples from existing companies and startups pitching their story for a future enterprise. Some vendors sell a solution based on their own product innovation platform, others on existing platforms and many new vendors are addressing a piece of the puzzle, to be connected through APIs or Microservices. I wrote about these challenges in Microservices, APIs, Platforms and PLM Services.  Remember, it took us “old PLM experts” more than 10-15 years to evolve from PDM towards PLM, riding on an old linear trajectory, caught up by a new wave of iterative and agile processes. Now we need a new generation of PLM experts (or evolving experts) that can combine the new concepts and filter out the nonsense.

Point 2

(Flip) But then given point 2: ‘Model-based enterprise transformations,’ in my view, a key effort for a successful PLM expert would also be to embed this change mgt. as a business process in the actual Enterprise Architecture. So he/she would need to understand and work out a ‘business-ontology’ (Dietz, 2006) or similar construct which facilitates at least a. business processes, b. Change (mgt.) processes, c. emerging (Mfg.) technologies, d. Data structures- and flows, e. implementation trajectory and sourcing.

And then do this from the PLM domain throughout the organization per optimization.  After all a product-oriented enterprise revolves around the success of its products, so eventually, all subsystems are affected by the makeup of the product lifecycle. Good PLM is a journey, not a trip. Or, does a PLM expert merely facilitates/controls this enterprise re-design process? And, what other enterprise ontologism tools and methods do you know of?

Only this question could be a next future blog post. Yes, it is crucial to define a business ontology to support the modern flow of information through an enterprise. Products become systems, depending on direct feedback from the market. Only this last sentence already requires a redefinition of change processes, responsibilities. Next, the change towards data-granularity introduces new ways of automation, which we will address in the upcoming years. Initiatives like Industry 4.0 / Smart Manufacturing / IIoT all contribute to that. And then there is the need to communicate around a model instead of following the old documents path. Read more about it in Digital PLM requires a Model-Based Enterprise. To close this point:  I am not aware of anyone who has already worked and published experiences on this topic, in particular in the context of PLM.

 

Point 3

(Flip) Where to draw the PLM line in a digital enterprise? I personally think this barrier will vanish as Product Lifecycle Management (as a paradigm, not necessarily as a software) will provide companies with continuity, profitability and competitive advantage in the early 21st century. The PLM monolith might remain, but supported by an array of micro services inside and outside the company (next to IoT, hopefully also external data sets).

I believe there is no need to draw a PLM line. As Peter’s article: Digitalisation enabled by product lifecycle management already illustrated there is a need for a product information backbone along the whole (circular) lifecycle, where product information can interact with other enterprise platforms, like CRM, ERP and MES and BI services. Sometimes we will see overlapping functionality, sometimes we will see the need to bridge the information through Microservices. As long as these bridges are data-driven and do not need manual handling/transformation of data, they fit in the future, lean digital enterprise.

Conclusion:

This can be an ongoing dialogue, diving into detailed topics of a modern PLM approach. I am curious to learn from my readers, how engaged they are in this topic? Do you still take part in PLM dialogues or do you consume? Do you have “tips and tricks” for those who want to shape the future of PLM?


Let your voice be heard! (and give Flip a break)

 

simpleMy recent posts were around the words Simple (PLM is not simple) and Simplicity  (Human Beings, PLM and Simplicity).  Combined with a blog dialogue with Oleg Shilovitsky (Small manufacturers and search of simple solutions)  and comments to these posts, the theme Simple has been discussed in various ways. Simple should not be confused with Simplicity. The conclusion: A PLM implementation should reduce complexity for an organization, aiming for increasing simplicity. The challenge: Achieving more simplicity is not simple (the picture related to this paragraph)

What does simplicity mean in the context of PLM?

My definition would be that compared to the current state, the future state should bring measurable benefits by reducing or eliminating non-value added activities. Typical non-value added PLM activities are collecting data from various disciplines to get a management understanding, conversion of file formats to support other disciplines or collecting and distributing data for change and approval processes.

If you can reduce or eliminate these steps, significant benefits can be achieved: reducing iterations, increasing quality and (re)acting faster to changes. These benefits are the whole idea behind Digital PLM. See Accenture’s explanation or read my post: Best Practices or Next Practices.DigitalPLM

Simplicity comes from the fact that the user does not need to depend on intermediate people or data formats to have an understanding of “the best so far truth.” Empowered users are a characteristic of modern digital processes. Empowered users need to have different skills than persons working in a traditional environment where exchange and availability of information are more controlled through communication between silos.  Some people can make the change, some will never make the change.

What can you do?

On LinkedIn, I found some good suggestions from Peter Weis in his CIO article: The most painful, gut-wrenching part of leading transformation. Peter’s post is about the challenges within a company going through a transformation and to keep the pace. My favorite part:

For me, the most difficult and gut-wrenching part of leading our transformation was not the technology involved. It was making and acting on those tough decisions about who was not going to succeed. In some cases, people had been with the company for decades and had been rewarded and encouraged for the very work they were no longer required to do. These were good people, skilled talent, who provided a great service to the company – but the technology and the cultural gap were just too wide for them to bridge.

Peter describes a dilemma that many of us consultants should face when implementing a business change. Keeping on board all employees is a mission impossible. But what if you want to keep them all on board?

Reducing complexity by making the system rigid?

One of the companies, I am currently working with, decided to keep all employees on board by demanding for a PLM system that is so rigid and automated that a user cannot make mistakes or wrong decisions. For example: Instead of allowing the user to decide which approval path should be chosen, the predefined workflow should be started where all participants are selected by automation. The idea: reducing the complexity for the (older) user. The user does not have to learn how to navigate in a new environment to decide what is the best option. There is always one option. Simple isn’t it?

I believe it reduces any user to a person that clicks on buttons and writes some comments. It is not about real empowerment.

There are two downsides to this approach

  • To make the PLM system, so incredibly rigid additional customizations are needed (which come with a cost). However more costly will be the upgrades in the future and the maintenance of every change in business process which is hard coded currently.
  • The system will be so rigid that even future, more digital native users, will dislike the system as it does not challenge them to think. Implementing the past or pushing for the future?

My challenge:

  • A rigid system creates the illusion that the system is secure and simple for the existing employees (who you do not want to challenge to change)
  • A rigid system leads by default to complexity in the future with high costs of change.

I am curious to learn how you would approach my challenge (a PLM consultant’s challenge)
Making the customer happy or being the “bad news” guy who creates fear for the future?
I assume a topic many PLM consultants should face nowadays – your opinion?

PLM can be swinging and inspiring although there will be times of frustration and stress when implementing. These seven musical views will help you to make it through the project.

 

One Vision

Every business change should start with a vision and a strategy. Defining the vision and keeping the vision alive is the responsibility of senior management. When it comes to PLM, the vision is crucial.

 

No more heroes

Of course, when implementing PLM, the target is to streamline the organization’s processes, eliminate bottlenecks and reduce dependencies on individuals. No more need for firefighters or other heroes because they fix or solve issues that appear due to the lack of processes and clarity.

 

Let´s do it together

PLM implementations are not IT-projects, where you install, configure and roll out an infrastructure based on one or more systems. Like a music band, it should be a well-orchestrated project between business experts and IT. Here´s a song to make your project swing.

 

Say NO at the right time

When implementing PLM, the software geeks can do everything for you: Customize the system, create a complete new environment looking like the old environment, and more. Of course, you will pay for it. Not only for the extra services, but also in the long-term to support all these customizations. Always try to find a balance between the standard functionality and infrastructure of the PLM system and the company´s vision. This means there are times you must Say NO to your users. Maybe not always as funny as these guys say it.

 

Eight days a week

During the PLM implementation and for sure after one of the several rollouts, changes may appear. And, normal work still needs to be done, sometimes in a different way. There will never be enough time to do everything perfect and fast, and it feels like you need more days in the week. When you are stressed, swing with these guys.

 

We are the champions

Then when the PLM project has been implemented successfully, there is a feeling of relief. It has been a tough time for the company and the PLM team. This should be the moment for the management to get everyone together in the stadium as an important change for the company´s future has been realized. Sing all together.

 

… But the times they are a-changing

Although a moment of relief is deserved, PLM implementations never end. The current infrastructure could be improved continuously due to better business understanding. However, globalization and digitalization will create new business challenges and opportunities at an extraordinarily fast pace. So, be aware and sing along with Bob.

 

BONUS

Time to close the 2016 book and look forward to next year’s activities. I wish all my readers happy holidays and a healthy, successful new year with a lot of dialogue, and no more one-liners.

 

See you in 2017 !!!!

clip_image002At this moment I am finalizing my session for PDT2016 where I will talk about the importance of accurate data. Earlier this year I wrote a post about that theme: The importance of accurate data. Act now!

My PDT session will be elaborating on this post, with a focus on why and how we need this change in day-to-day business happen. So if you are interested in a longer story and much more interesting topics to learn and discuss, come to Paris on 9 and 10 November.

Dreaming is free

Recently I found a cartoon on LinkedIn and shared it with my contacts, illustrating the optimistic view companies have when they are aiming to find the best solution for their business, going through an RFI phase, the RFP phase, and ultimately negotiation the final deal with the PLM solution provider or vendor. See the image below:

clip_image003

All credits to the author – I found this image here

The above cartoon gives a humoristic view of the (PLM) sales process (often true). In addition, I want to share a less optimistic view related to PLM implementations after the deal has been closed. Based on the PLM projects if have been coaching in the past, the majority of these projects became in stress mode once the stakeholders involved only focused on the software, the functions and features and centralizing data. Implementing the software without a business transformation caused a lot of discomfort.

clip_image005Users started to complain that the system did not allow them to do their day-to-day work in the same way. And they were right! They should have a new day-to-day work in the future, with different priorities based on the new PLM infrastructure.

This cultural change (and business change) was often not considered as the PLM system was implemented from an IT-perspective, not with a business perspective.

Over time, a better understanding of PLM and the fact that vendors and implementers have improved their portfolio and implementation skills, classical PLM implementations are now less disruptive.

A classical PLM implementation can be done quickly is because the system most of the time does not change the roles and responsibilities of people. Everyone remains working in his/her own silo. The difference: we store information in a central place so it can be found. And this approach would have worked if the world was not changing.

The digital enterprise transformation.

With the upcoming digitization and globalization of the market, enterprises are forced to adapt their business to become more customer-driven. This will have an impact on how PLM needs to be implemented. I wrote about this topic in my post: From a linear world to fast and circular. The modern digital enterprise has new roles and responsibilities and will eliminate roles and responsibilities that can be automated through a data-driven, rule-based approach. Therefore implementing PLM in a modern approach should be related (driven) by a business transformation and not the other way around!

Benefits realization

In the past two years, I have explained this story to all levels inside various organizations. And nobody disagreed. Redefining the processes, redefining roles was the priority. And we need a team to help people to make this change – these people are change management experts. The benefits diagram from Gartner as shown below was well understood, and most companies agreed the ambition should be to the top curve, in any case, stay above the red curve

clip_image007

But often reality relates to the first cartoon. In the majority of the implementations I have seen the past two years, the company did not want to invest in change management, defining the new process and new roles first for an optimum flow of information. They spent the entire budget on software and implementation services. With a minimum of staff, the technology was implemented based on existing processes – no change management at all. Disappointing, as short-term thinking destroyed the long-term vision and benefits were not as large as they had been dreaming.

Without changing business processes and cultural change management, the PLM team will fight against the organization, instead of surfing on the wave of new business opportunities and business growth.

Conclusion

If your company is planning to implement modern PLM which implicit requires a business transformation, make sure cultural change management is part of your plan and budget. It will bring the real ROI. Depending on your company´s legacy, if a business transformation is a mission impossible, it is sometimes easier to start a new business unit with new processes, new roles and potentially new people. Otherwise, the benefits will remain (too) low from your PLM implementation.

I am curious to learn your experience related to (the lack) of change management – how to include it into the real scope – your thoughts ?

Addition:
As a reaction to this post, Oleg Shilovitsky wrote a related blog post: PLM and the death spiral of cultural change.  See my response below to this post as it will contribute to the understanding of this post

Oleg, thanks for contributing to the theme of cultural change. Your post illustrates that my post was not clear enough, or perhaps too short. I do not believe PLM is that difficult because of technology, I would even claim that technology is a the bottom of my list of priorities. Not stating it is not important, but meaning that when you are converging with a company to a vision for PLM, you probably know the kind of technologies you are going to use.

The highest priority to my opinion is currently the business transformation companies need to go through in order to adapt their business to remain relevant in a digital world. The transformation will require companies to implement PLM in a different manner, less silo-oriented, more focus on value flows starting from the customer.

Working different means cultural change and a company needs to allocate time, budget and energy to that. The PLM implementation is supporting the cultural change not driving the cultural change.

And this is the biggest mistake I have seen everywhere. Management decides to implement a new PLM as the driver for cultural change, instead of the result of cultural change. And they reason this is done, is most of the time due to budget thinking as cultural change is ways more complex and expensive than a PLM implementation.

 

 

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.

The past weeks I have discussed at various events two topics that appeared to be different:

  • The change from an analogue, document-driven enterprise towards a digital, data-driven enterprise with all its effects. E.g. see From a linear world to fast and circular?
  • The change in generations upcoming. The behavior and the attitude of the analogue generation(s) and the difference in behavior from the digital generation(s).

During PDT2015 (a review of the conference here), we discussed all the visible trends that business in exponential changing in some industries due to digitalization and every cheaper technology. The question not answered during that conference was: How are we going to make this happen in your company?

HOW ?

Last week I spoke at a PLM forum in Athens and shared with the audience the opportunities for Greece to catch-up and become a digital service economy like Singapore. Here I pictured an idealistic path how this could happen (based on an ideal world where people think long-term).

A mission impossible, perhaps.

clip_image002

The primary challenge to move from analogue towards digital is to my opinion the difference in behavior of the analogue and digital generations (and I am generalizing of course)

The analogue generation has been educated that knowledge is power. Store all you know in your head or keep it in books close to you. Your job was depending on people needing you. Those who migrated to the digital world most of the time continued the same behavior. Keep information on your hard disk or mailbox. A job was designed for life and do not plan to share as your job might come at risk. Continuous education was not part of their work pattern. And it is this generation that is in power in most of the traditional businesses.

clip_image004

The digital generation has been educated (I hope so – not sure for every country) to gather information, digest and process it and come with a result. There is no need to store information in your head as there is already an information overflow. Store in your head methodology and practices to find and interpret data. The digital generation for sure wants a stable work environment but they already grew up with the mindset that there is no job for life, having seen several crises. It is all about being flexible and keep your skills up-to-date.

So we have the dilemma here that business is moving from analogue towards digital, where the analogue business represents the linear processes that the old generation was used to. Digital business is much more an iterative approach, acting and adapting on what happens around you. A perfect match for the digital generations.

A dilemma ?

Currently the old generation is leading and they will not easy step aside due to their classical education and behavior. We cannot expect behavior to change, just because it is logically explained. In that case, everyone would stop smoking or adopt other healthy standards.

clip_image006The dilemma reminded me of the Innovators Dilemma, a famous theory from Clayton Christensen, which also could apply to analogue and digital businesses. Read more about the Innovators Dilemma here in one of my older blog posts: The Innovator´s dilemma and PLM. You can replace the incumbent with the old analogue generation and the disruptive innovation comes from using digital platforms and information understood by the digital generation. If you follow this theory, it would mean old businesses would disappear and new businesses would pop-up and overtake the old companies. Interesting conclusion, however, will there be disruption everywhere?

Recently I saw Peter Sondergaard from Gartner presenting at Gartner Symposium/ITxpo 2015 in Orlando. In his keynote speech, he talked about the value of algorithms introducing first how companies should move from their traditional analogue business towards digital business in a bimodal approach. Have a read of the press release here.

If you have the chance to view his slick and impressive keynote video (approx. 30 minutes) you will understand it better. Great presentation. In the beginning Peter talks about the bimodal approach sustaining old, slowly dying analogue businesses and meanwhile building teams developing a digital business approach. The graph below says it all.

clip_image008

Interesting from this approach is that a company can evolve without being disrupted. Still my main question remains: Who will lead this change from the old analogue business towards modern digital business approach. Will it be the old generation coaching the new generation or will there be a natural evolution at the board level required before this process starts?

HOW ?

I have no conclusion this time as I am curious to your opinion. A shift in business is imminent, but HOW will companies / countries pick-up this shift?

Your thoughts or experiences ?

%d bloggers like this: