In the realm of digital transformation, data is a fundamental element, particularly in the energy sector. The concept of a centralized 'master data' is crucial, comprising materials, components, and information from various ERP tools, forming a comprehensive data hub. However, the current system is plagued by fragmentation and manual data entry, leading to errors and inefficiencies. Engineers, vendors, and asset owners are all affected by this disjointed approach. This calls for a reevaluation of data consolidation methods, particularly in engineering, to reduce downstream impacts on CRM and avoid costly manual interventions. The challenge is to balance the need for digital transformation with the complexities of the energy industry, striving for more efficient and error-free data management solutions.

For any form of digital transformation "data" is the key component. This focuses on a central "master data". We have emphasized on several occasions , in having a quality data that matters. Presently the energy sector has a very structured way to set up a master data , the one that uses all the materials, components, drawings, collection of sources from various ERP tools ( Resources, vendors , suppliers, project management, logistics, planning, scheduling) and aggregated or can be aggregated at one central location. However, have we focused on how fragmented this data system is, spread out over several system interfaces and above all this data is fed manually. Engineers have their own data which is not tapped by many solely kept to their internal engineering needs usually stashed in excel files, then followed by the vendors, and eventually who pays for this fragmentation ? The "Asset owner" !

How so? ... if delays happen .. engineers go through a delayed cycle, resources by and large are many , and finally all these manual data generation, consolidation and/ or maintenance, need to be taken care of ,depending upon the needs.

Let us then focus on consolidating the " Engineering" aspect of it, in a way that the downstream domino impacts that will eventually impact CRM would substantially reduce. Manually entering this " central master data" is certainly happening today , typically via various 3D CAD tools. Millions are already spent on the same. However, manual intervention of data entry at every location is certainly prone to massive errors, above all incumbent to increased resources, for checking purpose and thus this fragmentation eventually results into maintaining and consolidating this data.

Thus we question at what cost should this be done?

While we transition into a much larger broader energy industry, there are better solutions out there, then indeed comes in the "MAYA" phenoma of acceptance of these solutions, which then leads to bringing in the "change" & the " transformation culture", in an already snail paced industry. This requisite has now led to formation of the digital transformation teams.This then leads to further an argumentative approach of “what is wrong with the way we are proceeding right now?

Could we simply create a master data hub with our existing practices, let the engineers use their existing tools , while we can still create a digital twin , a central data repository etc..... but....

For starters:

1.      Data is at multiple locations which results into "duplication" & "errors". It all boils down to resources and cost to maintain that spread out and disconnected data.

2.      There needs to be the upfront governing rules and validation set based on the "ASSET" to support the master data.

3.      The upfront governance via dashboards necessary in planning the "asset" , if is provided via visualization 3D CAD model and with a robust architecture, is only beneficial.

4. The present fragmentation delays internal processes due to inter-dependencies, multiple disciplines - which are manually controlled, could they be avoided ? and if so , could we merge BIM concepts and extend it further with time dependent model allowing data collection?

What system / platform can we transform that into to achieve full " data traceability" & yet help one & all operate.

4.      Data should be interoperable with standard ERP solutions data, which is favorable to asset owners.

5.      Above all the platform should be a ‍

“Mine craft” for "asset" generation.

Having this " central qualitative data" hub and very scalable solution is absolutely essentially from ground principles to make it a very solid, robust platform.

Building over this scalable solution matures "the asset" towards a digital transformation journey.

Quality of meta data for the asset, not only focusing at

1. geometry ,
2. loading conditions,
3. design rules,
4. empirical design standards,
5. several key parameters

which will impact over the ERP data further downstream. This data collection will go on building over time , gradually.

An asset can be " analyzed" and " build" and " design", with various validations and governance rules , which makes it only more predictable and holistic.

so what is then impeding to accelerate this approach - the "shift of mindsets from traditional to changing digital method". In such evolving era, why utilize traditional entrenched fragmented approach , why not "empower" newer approaches ! After all we all will go down , without achieving our sustainable targets, then who are we to blame , traditional methods or inability to innovate ?