With a global focus on aging infrastructure and systems, and investment battles being fought from the boardroom down to ground level, isn’t it time we started working together? We already share best practice in asset investment planning at conferences, but what if organisations came together to work as a community – making best of use of data, enabling better and more transparent decisions, and balancing risk vs cost to improve our infrastructure? Tom Rowson, SEAMS’ Product Manager, explains the concept of Community Decision Analytics.

For small- to medium-sized asset rich organisations, getting started with decision analytics for asset investment planning can seem like an impossibly hard task. The data requirements are hard to meet when you can’t throw money at the problem, and the analytics process requires skills your organisation often doesn’t possess.

Now, SEAMS are knocking down the biggest barriers to entry into decision analytics with a collaborative working programme called ‘Community Decision Analytics’. It aims to address three of the most frequently identified concerns:

“I can’t afford to pay for decision analytics…”

Large, asset-rich utilities have big budgets for asset investment planning. They can afford dedicated teams of data scientists and planners, and can run special projects for gathering data, modelling performance, and optimising their investment strategy.

But what if your overall investment budget is too small to justify that kind of expense? How can you take advantage of the benefits of analytics?

“I don’t have enough data…”

Complex statistical analysis methods can give powerful insights into asset performance and deterioration. Models derived from big data mash-ups can show hidden trends which humans don’t even consider.

But what if you don’t have enough data to support a rigorous statistical analysis of the performance of your system? What if you don’t come close to meeting the minimum standards for ‘big data’?

“I don’t have analytical capability in my organisation…”

The smaller you are, the less likely it is you’ll have someone working in your planning department who has a strong analytical background. Large organisations have large talent pools, and the ability to attract new staff. But what if there are only a handful of you, and you’re overstretched already? What if you can’t employ anyone who can build statistical models of your system?

Three big problems, one simple answer… Working collaboratively.

For over 15 years, SEAMS has been supplying gold-standard decision analytics software to large utilities at an enterprise level. Time and time again, we’ve spoken to organisations who could benefit from our technology and services, but haven’t been able to take advantage. Often, the perception is that they cannot afford to commit the time and effort to engage with decision analytics software and processes. Their needs are immediate and, relative to the cost of entry into decision analytics, also small.

However, this shouldn’t mean companies on the smaller end of the scale can’t reap the benefits of advanced asset investment planning. If you can make the initial investment, the benefits are huge.

That’s why SEAMS is launching Community Decision Analytics. A completely new and collaborative way of working. To break down the three main barriers to entry into decision analytics, SEAMS are encouraging smaller companies in the same industry verticals to join forces and form a community. By pooling data and resources you can finally join the party.

How does it work?

Community Decision Analytics (CDA) requires subscribers to upload their data into a group data store. The data is anonymised on the way into the collective database, but you can continue to access your own individual organisation’s data in its original form. This overcomes the issue of having insufficient data to perform analytics, and also reduces costs, as you no longer have a need to increase data collection efforts.

The collected data is used to inform statistical analysis on the performance of asset types common to the community members, using methodologies developed by SEAMS’ data analysts. This means that all members of the community can benefit from years of analytics experience without requiring their own in-house analytic capability.

These generalised algorithms are then combined with each member’s own asset data to create a prediction model. This model can be combined with standard options for interventions to allow optimisation of investment strategy, with each member organisation having control over their own optimisation parameters (e.g budget limits).

 We aim to develop several communities over time; these will be defined by service type (for instance, water or rail) and along geographical lines.

For more information on Community Decision Analytics, or a chat about how it can help you, call us on +44 (0) 114 280 9000 or email us on contact@seamsltd.com