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Utilities and energy companies are rapidly adopting deeper and broader digitization to remain relevant to their customers and to respond to the changing parameters in the regulatory world. Solar arrays, large scale renewables, wind farms and the emergence of prosumers (customers generating and selling electricity) represent one of the shaping forces of the changing utility world. Disintermediation by vendors that allow large commercial and industrial accounts to disconnect from the grid by providing distributed generation and storage solutions represent the other force.
Caught between these two forces, those in the utility industry must quickly respond—and that response, to a large extent, has been the adoption of new technologies. In particular, this has included the renewed effort to further digitize all elements of the utility: generation, distribution, customer service, energy delivery, etc. This digitization is based on a collection of advanced technologies, such as:
• Internet of Things (IoT)
• Next generation Industrial Control Systems (ICS)
• Grid Edge Devices (SCADA, AMI, etc.)
• Analytics
• Machine Learning and Artificial Intelligence
• Digital Workflows and Robotic Process Automation (RPA)
"The CoE comes in by continually following the development of new tools, methodologies and techniques that all employees interested in analytics can use, across the company"
Utilities are embracing digitization in order to control cost and deliver innovative energy services in a world where customers ask for more choices and participation. This is a new challenge to utility employees, where customers are no longer satisfied by merely dialing into a call center, but measure service, support and convenience by comparison to the best on the web. The “Amazon experience” is becoming the expected standard in all areas.
For this reason, utilities have kicked off “digital utility” projects that embrace these new technologies and promise to deliver on their customers’ expectations around choice, price and service level. Yet these digital utility efforts can only be successful if they are also embraced and appropriately realized by employees in the utility.
This is the point where the world of fast moving digitization often meets a utility culture that has been shaped by decades of striving for perfect compliance with regulatory processes. This legacy culture is defined by behaviors which tend to favor risk-averseness over agility and experimentation, and insist on high precision and accuracy at the price of forward movement. The legacy culture also values hierarchical command and control structures over pushing authority and responsibility to the lowest level possible, closest to the customer and the equipment. In short, this is a culture that is no longer best suited for the demands of a digital utility.
The imperative therefore becomes: If utilities want to stay relevant by offering innovative, flexible solutions that meet customers where they are, they must match their advanced technology with an equally advanced culture and prepared workforce.
An imperative that is much easier stated than accomplished, since we are now looking not only at changing core technologies in the utility, but changing the culture along with it. Changing technology and culture—potentially at the same time—leads to questions such as:
• Do we first introduce the new technologies and then train our employees to be comfortable with them? (change management approach)
• Do we first empower our employees to execute agile methods and let them drive the new technologies? (agile approach)
• Do we drive this change simultaneously in all parts of the organization or do we lead with “pilots?”
One promising answer to these pertinent questions is adopting and rolling out the analytics function across the organization. Faced with the question of installing either a central analytics group or a decentralized group, an answer can be found by balancing a central Analytics Center of Excellence (CoE) with a distributed Community of Practice (CoP). While Analytics—under that name—is a relatively new field, practitioners close to the customer and the equipment have employed techniques and tools resembling analytics for decades. Reporting and data-driven decision making are by no means a recent invention.
It is therefore advisable to not centralize these “embedded” analytics experts, who bring their techniques to bear on their domain of knowledge, such as customer segmentation, renewable energies and distribution planning. Yet, these “distributed” experts suffer from not sharing insights and knowledge with each other. They also lack the time and resources to stay abreast of the newest tools and methods in the area of analytics.
The CoE comes in by continually following the development of new tools, methodologies and techniques that all employees interested in analytics can use, across the company. Further, the CoE organizes knowledge exchanges between the distributed experts to facilitate the dissemination of highly specialized insights from one end of the company to the other, by creating electronic and physical meeting places for the community of practice (CoP).
While this approach will not work universally, it represents one way to solve the dilemma of interaction between technology and culture change. By addressing these facets as one, we position employees to succeed in a rapidly evolving environment.
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