Can we still deal with the world we live in by reproducing the past?
Overview
The oil and gas industry has always been a complex sector that requires highly skilled and efficient business processes to run in place while abiding by the highest environment and safety protocols. For that reason, it was also one of the last industries to join the wave of digital transformation.
Globalization, competition, and technological advancement have made it feasible to produce items of all types more individually in recent years. New working methods like lean or agile have been developed and used in large numbers.
However, most of their efforts are focused on product development, which is merely the first stage in the overall product or service lifecycle management process. To explain this further, Traditional Business Process Management (BPM) techniques generate business processes statically, which means they typically adhere to a development time target specification (Design Time) (Bauernhansl, 2014). However, in order to properly place these items or services, a company must adhere to a few essential “success factors.”
The Golden Triangle as a Measure of Success
According to research, the golden triangle is one of the most important parts of any organization’s success from a strategic standpoint.
The three pillars of success are
quality,
cost,
and time.
When it comes to building and designing new business processes or enhancing existing ones, the focus should be solely on these three factors.
David Hutchison, in his book Product-Focused Software Process Improvement proves this point as he describes how to map a software development process into the business goals by applying a gap analysis, (Hutchison, 2014). His work shows that even in an organization with extreme dynamics, it is essential to optimize the process based on the golden triangle mentioned above, rather than only internal concerns such as happiness of employees or efficiency. These aspects are undeniably fundamental but should not be the focus for the optimization of the processes.
Innovation to improve quality and process optimization
Innovation focuses on the products and the services an organization has to offer. The innovation and creativity of the product team help to improve the functionalities and quality of the product or service. When it comes to markets, it is common to observe an unstable state at the beginning. Companies then require acting in a precarious situation. Many of the new ways of work like design thinking or lean development react to feedback from the community or internally directly into the product or service. An enterprise organization should not only respond to the product itself but must optimize the business processes within different layers and structures. It is here that we see the value of business process optimization. Max Weber (Weber, 1948) believes that after a certain amount of time the reaction should be again on the products and innovation rather than overengineering of the processes to avoid bureaucracy. Bureaucracy is one of the biggest trade-offs of business processes in general.
The primary and secondary organization
When we discourse concerning the business process, it is essential to know two different organizational structures. An organization structure that describes only the highest level of an enterprise itself is called the primary organization. The organization for each project or program in the primary organization is called a secondary organization, (Schwegmann & Laske, 2012). The primary organization is responsible for the routine and the core business structure. Routine is to reproduce the past and know that tomorrow will only be what it is today.
Corporate routine is not bad at all, but the problem is:
Can we still deal with the world we live in by reproducing the past? The answer is NO!
Especially in the aspect of continuous change in the competition world and customer journey, an organization needs to have a structure to react to these changes. An organization has its own sustainable life by defining the corporate high-level goals, vision, and missions with its routine and culture. At the same time, a structure to be able to react to the uncertainties and surprises, react to the changes and the challenges is the opposite of the reproduction of the habits.
When the time comes that the experiences an organization did in the past are not enough to lead the projects and programs to success by reproducing the skills in the past, we face a high uncertainty situation.
It is natural that personas sitting in the primary organization usually have more static roles and responsibilities in comparison with the secondary organization with more flexible and dynamic responsibilities.
Digitalization
A business model is a system of business elements and their relationships with each other. If we articulate this in a mathematical model, the transformation of business models involves a systematic change from system A to system A* by replacing or supplementing analogous elements or their relationships with digital ones. (Schallmo, et al., 2018)
For decades, interaction between people in the organization has been made analog. In earlier ages, even before having elementary digital communication, people interacted with each other through paperwork, verbal communication, and of course extensive and comprehensive documentation. The amount of work in creating a controller’s friendly documentation and paperwork was huge but necessary. It is interesting to see that even today, most companies produce a tremendous number of documents to avoid confusion or whatever value it brings. Digitalization is about the process of analog data and even a new way of generating the data we require1. For instance, it is common in software engineering to use technologies to create and update the documentation we had to write manually.
The networking of actors, such as companies and customers, is a step beyond all stages of the value chain. (Schallmo, 2016) The goal of “digital implementation” is the fulfillment of the most encouraging business model and the subsequent implementation within the company. (Schallmo, et al., 2018)
Airport Check-in process as an example
Our experience with the flight usually starts with checking in at the counter. If we have a piece of luggage to drop off, the person at the desk weighs the luggage, if it is at the range of the allowed amount, you get your boarding pass. If the luggage was heavier than allowed, you had to pay the penalty or reduce the weight of your luggage. It is a straightforward business process that everybody knows. But if your allowed weight was 23 kilos, what was the tolerance from the person seeing the meter? 23.01 was not allowed? How often have we observed people arguing with the person at the counter?
Since a couple of years, airlines have decided to digitalize the check-in journey to improve customer journeys. They started with the online check-in then and now with digital drop-off. If the machine is there, every rule should be pre-defined.
Is there any tolerance? Then it should be configured in the system.
Nobody will argue with the lady at the desk, and nobody feels underprivileged.
But at the end of the day, the airline saves millions by being capable of calculating the weight in advance, having less personal and fewer defects in the process and in the system.
In conclusion, even dehumanizing and decoupling communication will increase the value for customers and the organization. Also, again! It is coming back to the main success factors! Digitalization brings AI to make certain decisions and can let people focus on something with higher value.
Digital Roadmap in Gas Production – Asia’s biggest Gas Company
Introduction
I have been working since 2015, together with a large oil company in Asia. When I started in February 2015, the name of the department was “Integrated Operations” to bring different organizations within into the same picture, create the process within them, find digitalization potentials and help them to “Monitor,” “Analyze” and “Optimize” their work. I can map this into designing new secondary organizations with different goals.
For example, an operator operating wells within a field can read the meters at any time and monitor and control their technical equipment. The health of their staff is one thing; the amount of production is another thing.
Figure 2 Upstream high-level view
Let us have a more concrete example.
We are talking about gas production in this case. Two primary differentiations in the oil & gas domain are upstream and downstream business units.
Upstream is for producing oil or gas, and downstream is the customer to upstream and is processing the raw material into consumable products like motor oil or household gas.
Order is established from downstream to upstream in ordinary routine. It is the upstream’s responsibility to confirm delivery and make every effort to meet the agreed-upon delivery quantity. Otherwise, upstream will be liable for the non-fulfillment of the order it confirmed the previous day and will have to pay a penalty. A further contractual requirement is that the quality of the gas provided shall not exceed a certain level of CO2. For example, only CO2 emissions of 5% are permitted.
Figure 3 Downstream high-level view
We all realize the difficulty of gathering gas from a large number of wells and pipelines at a single location. Gas is piped in from various locations and then delivered to a terminal. Moreover, the gas is delivered to the terminal from tens of thousands of wells across the country. If the quality of the gas at the terminal is deemed poor, the additional CO2 must be retained before being sold downstream. You have no idea how much money is usually wasted in this transaction.
The Integrated Operations department came into the picture to optimize this process, reduce cost, and increase delivery time and quality. Also, it obviously targeted the golden triangle!
History & Challenges
In this way, the biggest challenge after the resilience of principal-oriented people is the amount of data available. As said earlier, operators of each well and field know about their data and the quality they produce, but making a decision based on the blended quality reaching the terminal was challenging. The organization tried to predict its best based on the history of the production. Still, it could not react quickly enough to avoid the off-spec scenario (Bad quality or quantity) altogether.
Another issue was the amount of time it takes for the gas to move through the pipelines. We cannot regard the system’s status as stable, and their impact should be estimated in relation to the gas’s transit duration. For example, if one field produces gas and transports it to the terminal in 18 hours while another field transports it in 4 hours, the impact on quality will be different.
Also, to make the long story short, the challenge was (and remains) real-time data and the ability to calculate mathematically and physically based on a dozen parameters and technical capabilities and limitations.
We set a huge goal:
Focus on the instrumentation of the equipment
Transfer the manual generated reports and readings from meters into digital numbers for the system to process.
An enterprise software solution to analyze the data and fill the missing data.
It was possible to save instrumentation and fill data gaps after using our enterprise software solution to apply mathematical and physical models. Even without a particular measurement, a comprehensive network and physical model can, of course, discover the unknown data in the system with high accuracy.
After years of implementation and business process optimization, we finally reached the full potential of surveillance of the whole system, analyzing the data and behavior of each field drilled down into the wells.
Digitalization Roadmap
Since the end of 2017, the company has experienced a fresh wave of digitalization. A new department called “Group Digital” has been formed, complete with a specialized team and digital leaders. The digital and cloud-first strategy has begun to scaffold. Later that year, the department’s name was changed to “Upstream Digital” from “Integrated Operations.” They now have a specialized change management team as well as a dedicated digital team that defines business capabilities and maps and separates them from “digital capabilities.” The objective for the next five years changes to have a matured digital culture.
The most significant prerequisite is still the data, its volume and quality. The author of this article worked for several clients from different industries such as Aviation and Logistics. It is all about data and giving sense into it. The author believes that we require to think about giving soul to the data and humanize the data as mentioned in (Hasenzagl, 2009).
In addition, the organization, like millions of other businesses around the world, sees the need to deliver insights into data, rather than just analyze and optimize it. Their plan is to collect as much data as possible, to store it in their own data lakes and data centers, to develop highly complicated mathematics and machine learning algorithm to automate hundreds of procedures, as well as to expand the quantity of artificial intelligence in the field. Also, collect data from the most basic levels of the company, connect the data, create insight, and distribute the knowledge to the field.
Our enterprise software, as previously noted, allowed those working in the control room to respond faster. With the new digital roadmap, AI will be able to make these judgments, freeing up human resources to work on more important tasks. Thus, even in the face of tremendous dynamics, the organization may maintain a structure that reacts to changes and uncertainty.
References
A Schallmo Hrsg, D. R. & Wagner Stefanie Kabel Hrsg, H., n.d. Schwerpunkt Business Model Innovation Mobilität 4.0-neue Geschäftsmodelle für Produkt-und Dienstleistungs-innovationen. s.l.:s.n.
Bauernhansl, T., 2014. Industrie 4.0 in Produktioan, Automatisierung. s.l.:s.n.
Gadatsch, A., 2010. Grundkurs Geschäftsprozess-Management. Methoden und Werkzeuge für die IT-Praxis: Eine Einführung für Studenten und Praktiker. s.l.:s.n.
Hasenzagl, R., 2009. Corporate Entrepreneurship und Veränderungs- methoden Zusammenfassung. pp. 305-336.
Hutchison, D., 2014. LNCS 8892 – Product-Focused Software Process Improvement. s.l.:s.n.
Schallmo, D. R., 2016. Jetzt digital transformieren. s.l.:s.n.
Schallmo, D., Reinhart, J. & Kuntz, E., 2018. Digitale Transformation von Geschäftsmodellen erfolgreich gestalten : Trends, Auswirkungen und Roadmap. s.l.:s.n.
Schallmo, D. et al., 2017. Digitale Transformation von Geschäftsmodellen. Grundlagen, Instrumente und Best Practices. herausgegeben von Daniel Schallmo, Andreas Rusnjak, Johanna Anzengruber, Thomas Werani, Michael Jünger.. s.l.:s.n.
Schwegmann, A. & Laske, M., 2012. Istmodellierung und Istanalyse. s.l.:s.n.
Teece, D. J. & Linden, G., 2017. Business models, value capture, and the digital enterprise. Journal of Organization Design, 6(1), p. 8.
[1] The author’s statement
[2] Slb.com
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