Robot with intelligent drawing 1

Apologies for the long delay in this follow up to the Laggards and Leaders article that I wrote and published a year ago, I got side tracked chasing an opportunity to do pragmatic digital transformation and it’s rather changed my view of things!

In my last post, laggards or leaders, I argued we (the industry) are laggards in the holistic view of asset lifecycle digital transformation, the reasons being:

  1. Project culture doesn’t foster innovation across contractual and organisation boundaries. We are too project centric rather than lifecycle centric.
  2. Our world is still too document centric, evidenced by the strong document control function and the weak information management function. We need to be object centric, where objects mean physical, logical and system components.
  3. Too much focus on technology being the answer, whereas it’s a small part of the answer and its use must be meshed in with the processes, people and DATA led not application led.
  4. We consider our assets very much as single businesses which makes enterprise wide adoption of digital asset strategies difficult. We are too asset centric rather than enterprise centric in our business models.

All these reasons are still valid in my view, but it’s been enlightening to have been involved in several new projects over the last year with companies making headway despite still experiencing all these deleterious traits and more.  This got me thinking about thought leadership and getting C level buy-in again and I concluded that C level buy-in is pretty much there or arriving very quickly, it’s execution which is lacking.

It seems to me we are stuck in a thought leadership hamster wheel with lots of people painting us the big picture and how much value there is in digital transformation. The slide below illustrates this perfectly.  I agree with everything on it but it doesn’t tell me HOW to do it or where to start.


I also admit I don’t find it helpful when the big technology companies promote technology as the answer to digital transformation, often repositioning existing products. Yes, technology is part of the answer but the solution is in the data.

So, my epiphany moment came, let’s not try and fix the system, it’s too large, slow and cumbersome.  Let’s not worry about thought leadership and the big picture but let’s do something fast, disruptive and effective at solving one of the above issues.  So we did and that’s why I have been slow in writing this. Here at DIGATEX we have been busy working hard on action leadership, pragmatically addressing the most significant problem hampering digital transformation. The massive volume of existing legacy non-intelligent documents and the fact that non-intelligent documents will be produced for many years to come is the biggest barrier, so we decided to focus on how to crack the document centricity problem.

We came at it from a different perspective.  Instead of seeing the documents as the problem we embraced documents and you will no longer hear me saying get rid of your document control department (sorry to all document controllers) and get rid of electronic paper. What we’ve done is create an AI platform to data mine documents to make them intelligent and integrate them into the digital world of objects, systems, information hubs, VR, etc.

Most s/w implementation around digital assets fails to achieve complete success because of the lack of quality, inconsistency and availability of data, which is of course entombed in electronic files, most notably PDF’s.  Historically, to fix this we have used sisyphean tasks such as single dimensional OCR, string aliasing, data mapping and so on and the relentless push for us to re-author everything into “intelligent” systems at great expense.  All these solutions are either costly, service intensive, slow and are only partially successful, very often leaving you back at square one.

However, what if we could teach a machine to read a document like a human, extract data in context and then analyse and process that data maintaining its connectivity to its originating document?  Then we have a real opportunity to create digitally intelligent documents and drawings which can then be exploited by any number of other technologies and assembled automatically into any form of digital asset.

Once you start down this route you solve peoples immediate problems in the real world fast, accurately and affordably. Now they know how many documents they have, their classification, revisions, if they are as-built or not, what tags are on them, what drawing references, what off-sheet connectors, engineering data, location data and so on.  All of a sudden documents become intelligent on their own, with all their rich content logged, organised and available for exploitation and the system keeps learning……… let’s teach it how to validate and check duplicated data, provide quality control, plan commissioning, decipher as-built dossiers, plan inspections. We can, because now we have digitally intelligent drawings and why stop there – let’s consider photogrammetric models, plain old photographs and point clouds too.

This is a fundamentally different approach to legacy asset information management which is to transform data from documents into another computer system with its own data structure. This often compounds the problem by creating yet another data source and is also used by vendors to lock you into their systems.

Our approach doesn’t displace these systems, it complements them, but with intelligent drawings it simply opens up new ways of exploiting data and you don’t need to convert them into some database system to do it.  Drawings simply co-exist with all their data and if something you hadn’t thought about is missed then ask the analytics platform and extract it.

Now that is what I call pragmatic and practical digital transformation and I am convinced this is the key foundation stone to creating a sustainable strategy for the digital asset.  If anyone is interested in a deeper discussion, please feel free to get in touch with me at