Lessons from ’08 Applied to ‘20 - Alpcan Efe Gencer


The 2008 Financial Crisis had severe implications on the banking and finance world, and one of them was certainly on how the industry conducted its business. People had always been at the epicenter of the financial world, whether they were on the trading floor or creating forecast scenarios. However, an aftermath analysis of how some banks managed to make it through those times reveals an interesting pattern. Banks that had gone the extra mile and invested in the latest generation technologies were aware of the situation of the non-performing loans through a series of algorithms that had alerted the managers beforehand. When the liquidity started to dry-up in the market, the machines had already unloaded a significant amount of their NPL’s. They were faster than their human counterparts in processing the sale orders into the market when the need to do so arose.

Some people in the industry even refer to the banks of our current era as being more of tech companies than the financial institutions of the past century. Indeed, if you look at the skillsets being looked for in the job applications, it is common nowadays to see knowing programming languages being a must. The amount of labor this has forced cut in the sector is another contributor to the increase in the Earnings-Per-Share numbers for the industry.

So how does this reflect on oil? Much like the effect ’08 had on banks, the 2020 Oil Crisis will likely force change the structure of how Oil&Gas companies operate, whether small or big. Throughout decades of operation, the O&G firms have focused exclusively on making drilling operations as lean as possible. This was largely because the energy firms had the underlying reserves booked on their financial sheets as assets, and they needed to turn them into producing assets and also to replace their lost barrels of reserves faster. Investor sentiment is likely to have held a large responsibility for this. While drilling operations have developed extensively, other areas of operation have been neglected to a certain degree, much as to how the banks have done in the past. The latest wave of large-scale digitalization in the industry has occurred in the 1990s, where the oil majors were acquiring one tech firm after the other to develop internal IT processes. But the real digital wave hit the world in the last decade, whether it was the developments of the Cloud systems, Artificial Intelligence, Machine Learning, Robotization, or Automation.


Sharing one common feat with the finance industry, that is having costly labor costs, the energy industry will likely resort to the application of companywide digitalization developments where they will be able to bring down the cost per employee to a minimum. There are already early adopters of this. The back-office jobs that usually curtail documentation and the reviewing of the said documentation are already being replaced by software designed to sort out the internally produced documents and automatically filter them out into the archives or flag for further human personnel review afterward. The cost benefits in the departments are said to be within the %75-%90 range compared to human-occupied positions—another point where there will likely be major changes in the usage of cloud technologies.

Currently, the industry is heavily reliant on keeping the data on physical servers on the premises of production. Being an extremely data-heavy industry, this is creating additional costs as the companies have to add servers on top of another one. In offshore environments, this is also taking away valuable space from the drilling operations on the platforms. At this point, we should remember that the underwater robots (ROV’s) the industry uses did not switch to digital formatting from analog formats until the late 2000s. The industry could be said to be slow to respond and adapt to certain matters. It should also be noted that a lot of the information being drawn away from the drilling is fragmented and requires labor-intensive processes to bring together and create interpretable datasets. If the conversion from the server-based system to cloud-based systems does materialize, we can expect to see AI’s to bring together the said documents, replace any faulty links in the datasets. If applied, machine learning can detect hidden links between wells or fields.

Improved safety of operations will also be achieved as the onboard personnel will have a wider variety of virtual training opportunities to use before getting on the drilling sites. If there is one segment of the industry where there will be visible changes in the near term, then it would be the trading department. Much like how the trading departments of banks have turned into digital High-Frequency Algorithms, the latest volatility in the financial commodity markets has shown valuable timing, and early analysis is. Robots can move and act in instances way faster than humans can, and the salaries in the trading departments can also run high for top talent in the industry. O&G companies will probably start their transformation from the back office as the front-office drilling prospects will likely be too expensive and complicated to handle in a short notice. Taking one step at a time, all industries reliant on keeping the shareholders content converge on the same topic, better Earnings-per-Share, and larger dividends.


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