Embracing Disruptive Technologies to Create Smart Business Processes
Big Data, Cloud, RFIDs, and Industrial Internet of Things (IIoT) are part of a digital transformation, a common theme which can be observed across many industries. It corresponds in the Upstream Oil & Gas industry to a broadening of the Digital Oil Field (called Integrated Operations as well) efforts our industry has undergone for the last fifteen years or so. The ultimate outcome is delivering a digital customer experience, unraveling historical and “real-time” data from applications, suppliers and customers, by correlating events in time and acting on them to enhance customer and enterprise value. This means embracing disruptive technologies to create smart business processes that transform the way we do business and drive improvements in efficiencies and effectiveness ultimately changing the customer experience.
Software, data, and analytics are central to a company’s ability to differentiate itself within the Oil and Gas industry and IIoT allows enterprises to simplify or at least standardize and accelerate the connection of their devices to a cloud (internal or external). The purpose is to provide machine operators and maintenance engineers with near real-time communication to schedule maintenance checks, improve machine efficiency, and reduce downtime. It is also used to inform their own product development teams to influence their activities and design. It can also lower costs of the service company’s service agreements (better ability to guarantee performance). Proactive identification of potential issues also takes the cost out of repairs and help manufacturers provide a better service.
We see the challenging times our industry is weathering as a possible catalyst to push service companies willing to differentiate themselves to adopt a new business model wherein they will provide more integrated services; taking example from the shift observed in other sectors such as the aviation industry where some actors have started selling thrust per hour instead of airplane turbines to the airlines. While the complexity of a field optimization involves many unknowns (and therefore uncertainties) that go well beyond the optimization of one device, the combination of traditional Oil & Gas model based simulations and analytics derived models may have a promising future.
“Software, data, and analytics are central to a company’s ability to differentiate itself within the Oil and Gas industry”
A more holistic data driven service approach could further impact the sales process that has already evolved with the implementation of Digital Oil Field projects; involving a wide range of expertise from subject matter experts related to the core activity being addressed to software and analytics experts. It requires being able to identify how the solution fits into the overall solution architecture of hardware, software, and service of the client.
A new business model linked to a new value proposition is emerging. The trend is moving towards a subscription model to commercialize software priced based on the value that they deliver. The remuneration could become partially outcome-based, evolving from a capital expenditure to a model that bundles equipment with service and software as an operational expense offering. Some service contracts already include equipment, services, software, and the relevant analytics and provide an incentive to improve efficiency or performance so that the service company is rewarded to a certain degree according to the results achieved. For an improvement of X, the provider is paid $1 and for an enhancement of X+ it gets $1.5 on top of a fixed retribution. We could observe more adoption of this type of commercial agreement. Operators should become more open to this type of arrangement to manage their risk exposure but these agreements would also require them to share the necessary data to establish the baseline measurements that makes the model work. Furthermore, when adopting an outcome-based pricing, operators will also need to cede some control to service companies as well as the data the service company has access to for it to assume its new role properly. Discussion around the operational influence the service company has in terms of calling for scheduled downtime and other decisions will need to be agreed upon.
Days of being seen solely as an equipment provider are counted. Software is a differentiator to be perceived as a suitable partner to contribute to the outcomes operators are set to deliver. We are morphing from assets under management to data under management. Managed services will deliver the greatest ROI and risk transfer to the service providers.
One challenge is getting engineers to trust the information and the systems build around the data feeds. Transparency as to how the data is being processed as well as education to these new methods can go a long way to facilitate this reliance.
On a broader level the challenge is reorganizing companies around a new way of doing business blurring artificial silos such as Operation Technology and Information Technology. We see the advent and generalization of near real time data collected, aggregated, validated, and transferred to be funneled into workflow processes which can aggregate these streams with unstructured data sources to then trigger back office operations as much as correcting settings on filed devices or altering the priorities of personnel.