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 ?
Last week I posted my first review of the PDT Europe conference. You can read the details here: 
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: 
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.
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.
Principle 1 The bimodal strategy as the image shows.
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.
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.
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.
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.
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.
As I am preparing my presentation for the upcoming 
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.
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.
Once data is able to flow, there will be another discussion: Who is responsible for which attributes. Bjørn Fidjeland from 
At this moment there are two approaches to implement PLM. The most common practice is item-centric and model-centric will be potentially the best practice for the future. Perhaps your company still using a method from the previous century called drawing-centric. In that case, you should read this post with even more attention as there are opportunities to improve.
However, in the beginning, the model can be still a functional or logical model. In particular, for complex products, model-based systems engineering might be the base for defining the solution. Actually, when we talk about products that interact with the outside world through software, we tend to call them systems. This explains that model-based systems engineering is getting more and more a recommended approach to make sure the product works as expected, fulfills all the needs for the product and creates a foundation for incremental innovation without starting from scratch.
Once we are able to control this collection of managed data concepts of digital twin or even virtual twin can be exploited linking data to a single instance in the field.
During my summer holidays, I read some fantastic books to relax the brain. 
Further down the book, Tom becomes a little grumpy and starts to complain about the Internet, Google and even about Wikipedia. These information resources provide so often fake or skin-deep information, which is not scientifically proven by experts. It reminded me of a conference that I attended in the early nineties of the previous century. An engineering society had organized this conference to discuss the issue that finite element analysis became more and more available to laymen. The affordable simulation software would be used by non-trained engineers, and they would make the wrong decisions. Constructions would fall down, machines would fail. Looking back now, we can see the liberation of finite element analysis leads to more usage of simulation technology providing better products and when really needed experts are still involved.
However, what is a PLM expert? Recently I wrote a post sharing the observation that a lot of PLM product – or IT-focused discussions miss the point of education (see 
July and August are the months that privileged people go on holiday. Depending on where you live and work it can be a long weekend or a long month. I plan to give my PLM twisted brain a break for two weeks. I am not sure if it will happen as Greek beaches always have inspired for philosophers. What do you think about “PLM on the beach”?
I believe we all get immune for the term “Digital Transformation” (11.400.000 hits on Google today). I have talked about digital transformation in the context many times too. Change is happening. The classic ways of working were based on documents, a container of information, captured on paper (very classical) or captured in a file (still current).
What we have learned from innovative companies is that a data-driven approach, where more granular information is stored uniquely as data objects instead of document containers bring huge benefits. Information objects can be shared where relevant along the product lifecycle and without the overhead of people creating and converting documents, the stakeholders become empowered as they can retrieve all information objects they desire (if allowed). We call this the digital thread.
Companies are learning now how to manage the dependencies between these two domains, as consistency of requirements and features of the products is required. Due to the fast pace of software changes, it is almost impossible to connect everything to the PLM product definition. PLM Vendors are working on concepts to connect PLM and ALM through different approaches. Other companies might believe that their software process is crucial and that the mechanical product becomes a commodity. Could you build a product innovation platform starting from the software platform which some of the old industry giants believe?
Does history repeat itself even in the PLM domain? The last week I have read various blog posts related to PLM and Small and Medium Enterprises (SME). A good summary of these thoughts can be found in Oleg Shilovitsky’s post: 
In 2006, Oleg and I worked @ SmarTeam where we defined and built a “Core PLM” solution, targeting mid-market companies. This core PLM solution called the SmarTeam Engineering Express (SNE) contained both pre-configured CAD-integrations as well as BOM practices (EBOM-MBOM). Combined with documented best practices, pre-configured methodology, and workflows this environment could be implemented relatively quick (if the implementer did not want to earn extra money on services ).
Interesting enough SmarTeam’s enterprise customers requested the same capabilities. It makes you realize there is no unique difference in PLM for mid-market companies and large enterprises. I believe the major difference is due to education, the company’s culture and where the PLM decision is made. Let’s explore
These new hires are normally not educated on standard PLM concepts like ECR, ECO, Configuration Management, PLM-ERP best practices (EBOM/MBOM). For an engineering study, these practices/processes are not considered as critical as it is about collaboration and not about skills. The PLM capabilities engineering students learn are the basic functionalities they need master when working with their (CAD) tools.
Of course, you can educate yourself on PLM. CIMdata is well-known for its training program, John Stark and others can educate you on PLM. Have a look at this interesting new startup 
Large enterprises usually have staff with a strategic task to work on standardized and optimized processes for the future. These people will discover and have time to be educated on the values of PLM, supported by strategic advisors that know the value of PLM. In these companies, the decisions made for PLM are top-down decisions. Usability, functions/features and costs are usually crucial for bottom-u
Tthe change from moving from a document-driven approach towards a data-driven approach to collect and store information is not the main concept behind a digital transformation. The data-driven approach is an enabler to connect directly to the customer and change the current business model from delivering products into a business model delivering services or even more advanced delivering experiences. Services and experiences create a closer relation to the customer, more loyalty, but also the challenge that you need to connect to the customer in such a way that the customer sees value. Otherwise, the customer will switch to another service or experience. The 
However, a year ago the problems started to become more frequent. I started to send log files illustrating where the error occurred. Still, the Garmin response was the same: “Please reset the device and update to the latest software.”
For me, the interaction with Garmin illustrates that the company internally is not yet digital transformed. The service desk probably has KPIs (Key Performance Indicators) related to their response time and problem resolution time. Although I can debate the response time, it is clear that the problem resolution approach: Update to the latest software and if this does not work swap to a new device is not increasing the knowledge from Garmin as a company what their customers are experiencing.
A must for a digital enterprise is to dive into customer issues and to connect them back to R&D, both for the hardware part and software part. Something a modern product manager would do. If a company is not able to understand the multidisciplinary dependencies and solve issues from the field (with some effort), they will keep on making the same mistakes again with new product launches and lose customers who are looking for a better experience.
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: 
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.
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 
(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. 
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 
(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: 
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