What is Digital Transformation?
#digitaltransformation is discussed in multiple articles, conference presentations and online forums in the Oil and Gas industry. IT executives are eager to present their progress in the deployment of #datascientists and #machinelearning. With many experienced geoscientists and engineers having left the major oil and gas upstream organizations, simplifications of the complex process for "out-of-the-box"solutions could lead to erroneous results. These are some of the warning signs which have to be observed to avoid possible failures of ML and AI deployments.Though usually, it is not a tool that fails but an operator who did not read the manual.
Instead of a#digitaltransformation phase in the Oil and Gas industry, I believe we should aim for #digitalmaturation. Today's computer hardware and digital connectivity solutions are capable of delivering on many IT promises of 1990'sand 2000's. A decade ago the possible delivery on these promises was costly to the organizations - this led many to manage their IT budgets by neglecting to implement a variety of the best software to solve individual problems and manage their massive trove of data. Instead, they elected to deploy generic commodity tools sold by large service and software organizations. Today, many solutions which were very costly only 2-3 years ago are an affordable reality.It's important that the industry not rush into #AI and #ML solutions without attaining the required domain knowledge and the ability to manage and use these tools responsibly - hence our industry needs more than a#digitaltransformation. It needs to achieve a #digitalmaturation, where logic and focused efforts prevail over the generalized and haphazard.
The Oil and Gas industry is tapping into the fundamental ML and AI science and research that has been ongoing in the medical and financial industries for the last decade -meaning a lot of the basics and fundamental structures have already been built and survived scrutiny. We are in a position to learn from the experiences of those industries and build upon systems that already exist and work well.Another consideration is cost - they can quickly mount, as most organizations have recently found out with their SAP deployments. Most SAP implementations I have observed carried the promise of being "out-of-the-box", but instead turned out to be a sequence of never ending customization projects.
Ultimately it is up to us, human beings, to take responsibility for and achieve #digitalmaturation, as well as to apply #AI and #ML in appropriate and justifiable ways. By using a new generation of software capable of delivering on expectations of the software performance and functionality at a reasonable cost augmenting human capabilities, we can achieve the #digitalmaturation. One must not forget the bottom line though: for most organizations, the value of new technology is obscured and cost reduction is the management driver behind many technology implementations. And therein, as the bard would say, lies the rub.
