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Portfolio decision-making

Prioritising utilities’ digital transformation projects and programs

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Effective portfolio analysis, planning and control are key to the health of any utility, but they quickly become complex in a dynamic environment.

Driven by changing environmental, regulatory, stakeholder and customer needs, as well as evolving risks, emerging technologies and disruptive players, utilities are seeking to use data to develop investment strategies and plans in the most fact-based, risk-managed, and resource- and cost-effective manner possible.

In unprecedented times like the COVID-19 crisis, data-driven decision-making is more important than ever. Utilities have substantial portfolios of work that are critical to assuring future power delivery and other strategic objectives, including grid modernisation, customer choice improvements and meeting electric vehicle demand. The crisis already impacts that portfolio as utilities cancel, defer, change and add work, even as work stops or slows because of lack of resources.

Many utilities are asking: How do we quickly assess our portfolios and re-prioritise the work that matters? What parameters do we need to consider?

We understand the urgency of these questions.

How our tool enables data-driven decision-making

Deciding where to start with innovation programs and investment is a challenge. Decision-making improves significantly when you reduce the gap between asking and answering critical investment and planning questions.

Our Portfolio Analyser & Optimisation Tool helps utilities make the right decisions as quickly as possible. The Portfolio Analyser runs real time analysis, visualising data to help clearly communicate outcomes to leadership and the broader organisation, which is critical in an evolving crisis such as COVID-19.

We combine sophisticated machine learning and traditional Monte Carlo probability models with simple data capture and visualisations to support corporate investment governance through the effective identification, analysis, prioritisation and planning of key projects assembled in portfolios.

The tools are most powerful when used in real time to examine alternatives, compare portfolios and conduct ‘what if’ analyses. This allows a meaningful discussion of investment scenarios, such as prioritising projects by any criteria, including business factors, changing risks, data status, funding levels, time, benefit type, category of investment and priority score.

The tools create a sharp focus on the criteria that matter most and can be deployed in most business contexts, from asset management and grid modernisation to customer operations and analytics.

  • Individual definitions of projects or use cases are captured along with specific business and data variables. These variables determine high-level risk, complexity, cost and effort to implement. These factors determine overall use case value, which is used in portfolio assembly.

  • Our tool generates portfolios with a click of a button and is designed to maximise return for a given portfolio cost envelope. An investment planner using the tool can apply adjustable constraints to the portfolio (such as total budget, budget allocation per year, capital expense and operational expense limits) and investments can be manually forced in or out of the portfolio, so the user has full control.

    Users of this tool have many options to tailor their portfolio at the project- and portfolio-level by adding constraints or adjusting features. For example, the tool enables:

    • editing to include and exclude projects and their component use case definitions
    • adjusting scoring system, constraints and valuation of the potential investments and other variables
    • forecasting the portfolio to best meet Capital or O&M future envelopes
    • direct comparison of portfolios to give a detailed view of the investment options available
    • visualisation of the overall portfolio and its content by any dimension of the investments.
  • The portfolio optimisation model is data-driven, and its interface lends itself to ease of access for a broad range of stakeholders. Data input and output is based on a standard data file that allows saving, comparison and editing within a browser or other tools, such as Excel. Data can be exported or imported (e.g. from Powerplant) from/to other systems using the standard template. The model is configurable at the functional, data variable and algorithm level and uses standard web frameworks. All data always sits on the user’s machine.

City of Calgary

Ensuring that consumers have equitable access to fairly priced utilities is a key goal for regulators and local and city governments. We supported the City of Calgary in reviewing pricing in an IT outsourcing contract for a natural gas and electric utility.

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Gregg Edeson

PA energy and utilities expert