Pattern Lab

Digital Transformation - Understanding the "How"

In our previous blog post, we’ve explored the importance of establishing the reason (i.e. the “Why”) to rally the organization to transform with Digital. The “How”, arguably the most difficult and complex piece to orchestrate can be encapsulated with a mindset of “Think BIG, Start small, Scale fast”.  
“Think BIG, Start small, Scale fast” is and can be more than a catch phrase. Most people consider the concept in a linear fashion – think and strategize first, start with experiments and then scale successful initiatives quickly. Repeat this pattern enough times and you have a Digital Transformation. Sounds simple but reality is much more complex. In this blog post, we will examine the enablers to put in place to coordinate all the thinking, experimenting and scaling. 
Think BIG. At the macro level, it is the vision. At the micro level for each domain, it is the workflows that needs to be improved/changed to fulfill the wider vision. A well though-out think BIG blueprint identifies the value leakages and bottlenecks in the value chain and workflows that needs to be attacked in a systematic manner to drive improvements. For example, you can employ AI to significantly improve seismic interpretation but that is pointless if the large amounts of data cannot be processed with limited on-prem computing capabilities.  
Start small. It is a paradigm shift in thinking that you can do and self-correct along the way. A lot of projects fall under the weight of their ambition to cover 100% of the requirements and satisfy all stakeholders in one go. If you simplify and break the problem in smaller chunks, progress can be made quicker – but you still need to think ahead. 
For example, a Risk Based Inspection (RBI) program to optimize maintenance intervals typically starts with a large study of all asset types involving a big committee before solution development and “big bang” launch globally. Alternatively, would it be better to focus RBI on a specific equipment for a production platform first? You can focus on developing the solution and chase down the value levers in terms of maintenance schedule, spare parts and suppliers? Incidentally, some teams declare victory too quickly at the analytical stage – value is only captured when the maintenance schedule and call-off is duly changed (where the schedule provides further insights to the next material equipment to focus on). “Further enhancements” are then made to accommodate other equipment and “scaling” the same solution/methodology (with required modifications) to another production platform. 
Start small does not indemnify the need to think BIG. Traditionally, E&P companies systematically identify and resource/fund the projects (and experiments) through a heavy CVP (Capital Value Process with FEL) process geared towards multi-million/billion capital programs.  
For digital projects, some companies including Schlumberger employ Critical Decision Points (CDP) and Season Based Governance (SBG) processes. Each domain (and cross domain) champion strategized and orchestrates the many agile projects through this governance process towards the vision. The roadmap for Exploration (e.g. extremely data intensive, less stakeholders) and Production (e.g. less data intensive, complex stakeholder set with large installed base of legacy physical assets and systems) can look very different.  
Also, not all solutions need to be built from scratch – there are opportunities to leverage commercial solutions in the market, where the focus on the initiative is in evaluating, modifying, adopting the embedding these solutions into the organization to accelerate value delivery. The governance process ensures all initiatives work towards the vision (think BIG) and channels resources and investments appropriately.  
Scale fast. Easier said than done. Many companies find scaling successful experiments/initiatives (often in small controlled context) organization wide the single largest challenge when faced with the wider global reality of data (availability, inconsistency, quality), installed base (infrastructure, IT/OT setup, legacy systems) and working methods (catering to different workflows in different regions with different stakeholders).  
You need to enable the ability to scale fast. This includes the new ways of working (including the governance process noted earlier to think BIG and start small) and the data ecosystem (including enterprise architecture and IT/OT infrastructure). The data ecosystem is an integral part of the Digital Transformation with advancements to leverage the cloud to scale, provide simulation/optimization capabilities and facilitate AI/ML workflows whilst ensuring cyber security. In E&P, the OSDU (Open Subsurface Data Universe) provides a game changer in the liberation and connectivity of data across the organization and industry (including suppliers) whilst maintaining the ability of each company to differentiate in the tools and solutions to use make faster and better decisions. 
The complex nature of Digital Transformation in E&P can be made simple if the individual elements and interdependencies are understood. You are not alone. Many companies and partnering/collaboration (refer to blog post Energized by Collaboration) make that step change in domain innovation as well as data ecosystem and IT/OT infrastructure.  

Author information: Alvin See is known as the keeper of trivia and obscure stories to his friends and colleagues. An engineer and business consultant, his passion is in the digitalization of the energy sector and the house he is living in.

Alvin See

Alvin See

Digital Transformation Guru


Useful links:

Digital Transformation Consulting