There is much talk about the value of data in our sector and about its ownership, possession or accessibility. When those key areas aren’t well understood, future data gaps arise and these could be mission critical or at least expensive to fix.
Where do we start to ensure against future data gaps? Ensuring the ownership, possession and accessibility of all data generated by or on behalf of the organisation is overkill and a massive project. We would recommend ‘keeping it simple’; our own consulting exercises start by splitting these types of projects into three stages:
- An audit of the current status;
- The identification and categorisation of data needs;
- Rationalisation of repositories.
By stage three, ownership, possession and accessibility can be taken forward, confident that the data can be housed and controlled in an appropriate, well-structured and segmented warehouse of data.
1. An audit of the current status
Most housing providers already have a plethora of data in their possession or held by third parties. Unfortunately, much of the data isn’t codified or shared, being held in the heads of employees, third parties, spreadsheets or systems that render it barely useful to support future decision-making.
An audit of these data sources should cover its provenance and reliability. Apart from the stated purpose, such data audits can uncover problems and solutions with existing uses and collation as well as identifying wasteful practices, without the need for expensive business process reviews.
2. The identification & categorisation of data needs
The second difficulty with these projects is to predict the data (and information) that will help the organisation going forward. There’s no textbook answer to this because it depends on the ambitions and requirements of each organisation. Desktop research, brainstorming, critical analysis and an investigation of predicted needs are the best way to build the hypothesis, but many advisors suggest requirements based on their own experience and knowledge as a less expensive alternative.
A basic example of the drawbacks to this latter approach is common in the sector: a stock condition survey should obviously be based on the defined data needs of the customer and their asset management system (assuming it is fit for purpose). However, we still see occasions where surveys are designed by the surveyors commissioned to execute them, without due regard to the customer’s asset management system’s needs. It is then left to the customer to shoehorn the results into their system for processing. While accepting that surveyors or customers may suggest valid additions to surveys defined from the asset management system, data gaps or poorly-matched data can undermine the outputs from that system and future decisions on which they are based.
This example is in a well-understood area of activity, yet it persists. With future data needs, everyone is a newcomer. Capturing and using the outputs from intelligent components, accommodating AI and unleashing the potential of predictive analytics are less well-understood areas of data. While we can all envisage potential future information sources, we should return to the ‘keep it simple’ premise because data can be expensive to collect, collate, interpret and act on. Hence, identifying those areas where data can add real value is crucial, and the ongoing monitoring of emerging needs goes hand-in-hand with this.
We’re all aware of the potential benefits of, for example, identifying component failure signals, monitoring tenant behaviours, complaints, asset usage and comparative information on product lifecycles, yet there are still difficulties with disrepair problems and avoiding them further down the line. If your future data can reduce workloads, costs or customer dissatisfaction it can be of benefit, but if marginal improvements create major new administrative burdens, they may not be feasible without significant business system reviews and improvements. Again, ‘keep it simple’ and look for big wins, with a properly measured realisation of costs and benefits.
Setting up a usable data bank (i.e. reliable, good provenance, complete, without errors and so on) must be carefully planned to ensure data resolves these predicted problems of the future, which also establishes for us how we address the problems of ownership, possession or accessibility.
With third parties, ownership and possession must be secured contractually. Obviously, contractors and advisors will prefer to use their own systems. This isn’t always a problem but where such data is deemed to have key future potential use, it needs to be either passed to the customer’s systems or contractors must use the customer’s systems in their work. Regardless of the size of a supplier, they can become insolvent and the underlying data lost to the customer. If we look at the more recent issues of repatriating EPC lodgement data from our government, there has to be a trust ‘nobody attitude’ to key data security.
3. Rationalisation of repositories
This area is simple to contemplate yet complex to implement. Not every IT system in an organisation allows full access to raw data but most modern systems allow users to design reports to output data to other systems for the BI uses we’re considering here. Often, it may be effortless to combine data from more than one system for onward analysis and reporting using modern BI systems such as Microsoft’s, but there may be legacy systems being fed with irrecoverable data of importance. With data being such an expensive investment, its accessibility even in the organisation’s own systems must be considered.
These three simple key stages (an audit of the current status, the identification and categorisation of data needs and rationalisation of repositories) allow an organisation to drive its own future rather than be drawn into ad-hoc headline ‘flavour of the month’ initiatives as the only progressive strategy. This doesn’t mean discounting such initiatives but embodying them into a strategic business case for future data usage.
Rachel Ratty is the sales and marketing director at Asprey Management Solutions.
