As described in our last post from last October (yeah – it’s been too long), we decided to figure out how SkenarioLabs’ analytics & approach could be applied in the public sector solving the important challenges around the renovation debt of the properties owned by Finnish cities. As we are solving similar problems with our clients in the private sector, this was definitely an interesting opportunity to look at. The opportunity is intriguing for us even acknowledging the fact that the criteria or objectives in managing a portfolio in the public sector – in many cases – varies notably from the private sector. After over a quarter of a year looking into Finnish cities’ portfolios, with the support of Kira-Digi-program, we thought it would be good to summarise on key finding so far:
There’s an actual problem to be solved here and were solving it.
When cities make decisions on which of their properties to renovate and invest, they seldom have a clear picture of the full-scale effects or how and where one can see the long-term results of an investment. Usually, the decisions are made for known or emerging issues without acknowledging the potentially lurking technical o health risks in the city-owned properties for the future years. This is certainly understandable as mapping the actual clear picture takes so many resources and time with the traditional methods such as technical surveys or building consultancy.
SkenarioLabs’ analytics gives a detailed and reliable answer to the following question: If this is my budget and these are my objectives to manage my property portfolio, which properties should we invest in and why? We answer this question with data-analytics and taking into account cities own characteristics including technical state of the properties, service network factors, energy efficiency factors, euros and health aspects. And Finnish cities are getting onboard: We started off with two cities for a pilot, got really encouraging results, updated our offering and now we have 20 cities onboard (in few months) utilising or committed to utilise our approach in managing their property portfolios. Naturally, our method will be further developed as the property data starts to pile in and our cases go further, but at this point, this looks very good.
More on this and other applications of our analytics in the next post.
Photo by Markus Koljonen (CC BY-SA 3.0)