Smart meters demand smart deployment

Smart meters are a smart idea, but consider the nightmare scenario: thousands of angry customers calling because they have yet to receive the new smart meters...

Smart meters are a smart idea, but consider the nightmare scenario: thousands of angry customers calling because they have yet to receive the new smart meters two days after the promised delivery; lines of service vans clogging up traffic and not at customers' homes; the anticipated cost savings and green credentials rapidly disappearing with the scheme's credibility, writes Simon Morris, vice-president of marketing at ClickSoftware.

The public are more likely to trust this new, seemingly complex technology if the deployment matches the hype. The logistics are Herculean; an as-yet non-existent workforce is to install and connect 47 million smart meters across the UK by 2020. And this relies on the public to provide access to properties and an array of partners to come together in concert.

Plenty of previous high-profile IT projects have ended in embarrassment. However, there is now an opportunity for electric utilities to make this deployment a success.

Planning for the rollout should begin now. One of the most important things to establish is the likely project team needed. Years of historical data from ordinary meter replacement projects and ongoing maintenance can be used to estimate accurately the manpower needed on the ground.

The spike in demand will of course require a huge influx of installation engineers and project managers into the industry. This in itself raises a number of important questions. Pre-implementation utilities need to consider where these extra resources will be sourced from in the middle of a utilities skills crisis.

Should there be a recruitment drive, should existing engineers be re-trained or relocated, and what should be the role of sub-contractors? During the implementation how should the rollout be structured, and how will this disparate workforce be controlled to get the job done in an optimal fashion? And finally what will happen to the workforce after deployment of the meters?

Some of these questions can be answered with high accuracy; the response to others is less clear and must be estimated. Such uncertainties require risk management, contingency planning, sensitivity analysis and playing out "what-if" scenarios.

Once the project begins thousands of mobile workers will face daily thousands of project-delaying banana skins, such as traffic jams, sick workers, undelivered parts, and customers not being at home. Scheduling systems can help control this by crunching complex algorithms and scenarios to optimise the schedule and deal with the unexpected on the fly.

Utilities should also capitalise on the maturation of mobile technology for two-way communication with installation engineers in the field. Schedule and customer data can be provided to the technician, and the technician can update project progress remotely. This will help speed the ascent of an undoubtedly steep learning curve by measuring collected information against the plan.

This can tell what is the efficiency of the workforce in the first month, or after several months. It can help say what impact the added workload has on response time to other customer requests and on budgets etc. Understanding these issues with more clarity will allow strategy changes to be made where necessary and delays to be communicated quickly and openly.

Given the political, economic, social and environmental importance of smart meters, the deployment on time and on budget should be more than a vague hope. Early planning, data capture, analysis and the ability to react quickly will make it a smart deployment.

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