New rules for utility portfolio management with data analytics

How utilities are becoming more innovative

Most posts on this blog describe innovation portfolio management. Portfolio’s of innovation ventures, new product & business development projects, and R&D require frequent updates. In the past two years, I have also witnessed the dynamics of other portfolio’s change, in more traditional sectors such as real estate and utilities.

In a recent round table at Bicore, we discussed the changing landscape of asset portfolio management at utility companies, such as telco’s, gas companies, and water companies. These utilities have large asset networks for which they have, traditionally, built stable long-term maintenance and overhaul portfolio’s. In  a discussion with experts representing Brabant Water, Vitens, Gasunie, Alliander, as well as foreign utilities, the trend to more innovation in their asset portfolio management was fully recognized by all. New techniques and tools are applied in the areas of data analytics (including big data and predictive modeling), of management control (such as network visualization, management dashboards, control towers), and of inspection (from drones, robots, to sensors).


Since the participants in this meeting were unanimous in their interest for further exploration of the implications, I put together this blog post to support this.

Main drivers for a new portfolio management approach

The following three main drivers for portfolio management were identified:

  1. Network safety and reliability of delivery
    This has always been priority #1 for these critical infrastructures. Costs and innovation were always second to this overarching driver, which led to management practices, culture, and processes and tools that emphasized stability over change.
  2. Cost efficiency
    Increased competition as well as cost benchmarking has led to increased scrutiny of various stakeholders (from industry clients to consumer protection authorities). In a typical reflex to address efficiency while maintaining reliability, long-term fixed planning practices appear: when project work can be fixed for several years to come, resource allocation can be optimized, with procurement and planning synergies maximized.
  3. Increased dynamics
    However, the context in which utilities need to deliver is changing more and more rapidly. A typical example is the changed formal policy of the Dutch government from focusing on gas as the main supply of household energy to a gasless future in less than two years. All utilities deal with increased pressure from new entrants, consumer demands for service flexibility and transparency, and policy makers need for more coordinated work in the public space (especially underground).

Information Technology: source of problems and solutions

By putting intelligence (IT) in the asset network, all utilities are on a path to build big data collections of asset and network behavior. Smart analytics of this data is on all of their agenda’s, and the new field of data science brings the techniques for step changes in network analytics. As indicated in our Round Table, the current state of the art seems to be that these analyses are run by experts for supporting their recommendations. The direct connection to portfolio management is still missing: most use case examples (and software tools) present one analysis and its recommendations, such as replacement of older material piping by more future-proof materials in the smartest way. This may meet drivers #1 and #2 above, but does not deal with change.

The multitude of analytical options, and the ongoing learning cycle that comes from gathering more data also makes dynamic portfolio management a more visible requirement.

In addition to new insights from analytics, it is clear that a lot of expertise is available in the asset management organizations and the supply chains. Data analytics should be set up to enhance or complement this human expert knowledge rather than replace it. However, proper tooling for this combination is less than mature.

(If you figured that the Internet of Things sensors and actuators in the asset networks themselves pose both a opportunity and a threat: yes, we touched upon this but did not embed this in the portfolio management process yet. Let me know if you have suggestions).

What is this new portfolio management approach?

In the utility company of the future, the portfolio management process is optimized to address all three drivers. The following practices should be part of that process:

  • the portfolio strategy is defined with objectives for safety and reliability, for cost efficiency, and for agility (responsive to change), with proper KPI-s
  • a continuous process of data analytics identifies smart improvement opportunities in new projects as well as in plannend or even running  projects (feed forward as well as feedback)
  • projects are defined and executed in such a way that continued new insights can be included
  • insights are created from both analytics as well as from expert elicitation
  • predictive models are checked and improved by monitoring data during project execution, and closing feedback cycles
  • these opportunities as well as the running projects are assessed in terms of their contribution to the portfolio KPI-s
  • scenario’s for portfolio updates are presented to decision-makers in time and in a format well-suited for decision making
  • the portfolio management process is sufficiently short-cyclic to make real project start and stop decisions in time
  • portfolio performance is evaluated against targets, benchmarks, and stakeholder expectations, and learnings are included

It seems clear that traditional annual portfolio planning & budgeting cycles tied to long-term and detailed project planning systems do not align with this approach. A more subtle issue may be on the culture side. In a world where a project’s added value may not be linked to fixed deliverables, the project teams must be much more sensitive to change triggers. Where traditional engineering project management practices have (and rightly so) focused on minimizing change and being less focused on benefits and more on delivery.

What are the next steps?


A practical step to make is to set up a portfolio management decision making process with appropriate frequency, and bring in the intelligence from data analytics directly as management information. A specialized and analytically strong portfolio management tool such as FLIGHTMAP is a good candidate as a stepping stone for this new approach.

We are looking to discuss with utility experts how this is best done, and which further process and tool setup support the culture, process, and practice change needed to address the new world. Let me know your thoughts?




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