In the last year or more, we have heard the Prime Minister time and time again declare that Government is “following the science”, whilst millions of citizens have found themselves spending time staring at charts and monitoring trends. During this time, the link between the data that government collects and the outcomes it drives has suddenly assumed a place at the forefront of public consciousness.
The phrase “Data Saves Lives” has long been a clarion call for those of us seeking to realize and unlock the value public sector organizations hold in their data. While the concept has perhaps never felt more prescient, it’s not only in times of unprecedented uncertainty that the value in public sector data comes to the fore.
There are pressing questions that the public sector has been grappling with before Covid-19 that will continue to challenge us as we emerge from the pandemic. How do we deliver better care for an aging population with changing needs? How do we predict and prevent threats to public safety? How do we move around the country more efficiently and arrest the damage we are doing to our environment?
The data that public sector organizations have available can help provide these answers, and that alone is invaluable.
Why value public sector data?
It’s no secret that budgets are not endless, and the difficulty in explaining and proving the return on data investment is a real challenge. It is probably the number one reason to get serious about defining and measuring the value in your data, but it is not alone.
Other reasons to consider include:
1. To prioritize action
When it comes to choosing which elements of a data strategy to invest in, choices need to be made. These should be informed by the value each initiative will individually or collectively unlock.
The answer for which actions to prioritize should lie in a clear understanding of the route to value. Not all data is equal when it comes to delivering your strategic objectives, you will need to prioritize and be able to defend those decisions to those who would have preferred you start with their area instead.
2. To measure the effectiveness of the actions you take to improve it
Just like everyone else, us data folk should be held to account for the investments that are made in improving data itself (collection, curation, quality etc.) or the methods used to extract its value (analytics, digital applications etc.).
Without a baseline of the value in our data, how can we persuasively present a case for the improvements we have made over time? The answer is we cannot – providing a clear need to value your data assets and revisit those valuations over time.
3. To monetize it
Not everyone will feel comfortable with the idea that public sector data assets could be commercialized in a straightforward transactional sense, but it is unlikely to go away. The world’s wealthiest companies are data companies. Make no mistake the value in public sector data assets to those companies is monumental. It is data they can only approximate from all the other sources they mine.
In a hypothetical scenario whereby a local or regional authority were to look to monetize its data, you’d want a fair price, to be assured that value is fully understood, and the best deal negotiated. This will not happen without measuring value.
How can a value be put on public sector data?
1. Cost Value of Data
The cost to the organization of collecting, managing, protecting and storing data, including people, process and technology costs. When you factor in the people and technology elements, it is indeed a costly endeavor.
The asset that those elements fundamentally store, manage, protect, move and analyze is data. If you’re looking for a compelling statistic to use to get your investments in data as an asset taken seriously, working out how much your organization currently spends looking after it, is a good way to get some attention.
Presenting your plan as an incremental investment (often a small percentage) to get better bang for the significant buck already committed, is a technique frequently used by those responsible for other strategic assets. The sell can take many forms, it might be that you will drive process efficiencies or performance improvements elsewhere in the organization, or that you can identify savings and efficiencies within the current data spend portfolio but need to land an invest to save proposition.
2. Economic Value of Data
That is, the benefit generated, less the cost of the intervention itself.
Using a logic chain to address the bridge example you would have five buckets of considerations. The inputs, activities, outputs, outcomes, impacts. The first two columns are the things that cost money and the latter three particularly the last two, are the things that either save or generate money (benefit). In the bridge example, you tot up the inputs e.g. materials and the activities e.g. construction, administration, maintenance etc and these are your costs of the intervention. You then look at the outputs e.g. the bridge itself, regeneration of surrounding land, followed by the outcomes e.g. faster journey times, less congestion, new jobs, new business start-ups and new revenue streams and the impacts (usually directional) e.g. net additional GVA, reduced CO2 emissions, increased local employment, net additional returns to the exchequer etc.
In this context the Economic Value is the difference between those costs and benefits.
Applying this type of framework to a data related initiative is often more difficult. In commercial settings, it can be achieved through testing e.g. make data available to sales team ‘a’ through a new BI platform but not to sales team ‘b’ — measure the difference in performance and you have a measure of value returned for your investment.
When we do this with government organizations, we tend to look at unit costs as being the most effective scaling factor for the benefits unlocked. I was part of a project a few years ago where the client had an issue with delayed transfers of care from an acute hospital setting into community settings, congested wards, patients in limbo and adverse outcomes were all symptoms of what at least in part was a data problem. Neither party in the discharge process had visibility of the other’s data. Acute settings didn’t know when spaces would become available to discharge patients into, and brokerage teams had no real advance view of how many patients with which types of need they were going to need to support.
The intervention was to create a live link between two systems to facilitate the exchange of data; a portal to view it through and engage the respective teams to ensure that relevant data protection principles were considered. The inputs (both data and technological), activities (drafting and reviewing a DPIA, configuring and testing the live link, designing and building the portal) formed the costs (c£100k). The outputs, e.g. improved patient health outcomes, reduced incidents of delays in transfer of care and improved staff morale were some of the benefits. More strikingly were the number of bed days released, to which the NHS ascribes a unit cost. In total, conservative efforts suggested the trust was able to save £150,000 per month in bed days. This is a powerful example of how investing in a data and insights project effectively could yield real tangible and positive impacts.
3. Opportunity Cost Value of Data
The cost of unrealized value due to the “state” of the data asset. This can be measured using the opportunity cost of investments already made or outcomes not achieved.
Imagine your organization has made a £20m investment in a new technology platform. You were persuaded to go for the Rolls Royce version with all the bells and whistles, reassured that concerns over the data in legacy platforms were nothing the vendor hadn’t seen before and that their solution would fix all of that anyway. Two years in and only 60 percent of the functionality has been enabled. Your vendor is blaming the state of your data. The state of your data is therefore costing you £8m.
4. Market Value
There are many means via which government can understand the market value of its data. Think about the partnerships being struck around innovative new technologies between public and private sectors. Often the public sector provides the data whilst the private sector provides the means to turn it into insight and action. I believe we will see more and more of this type of “joint venture” going forwards and we’ll very quickly come to think of public sector data as a magnet to pull in private sector investment.
Data is not finite and so the opportunity to repeatedly sweat the same asset through such deals is much greater. Not forgetting legitimate concerns around the ethics of using government data in this way, but there are ways to navigate those and end up at this reality sooner than we think.
However, these approaches are not designed to be mutually exclusive. To go toe-to-toe with other investment priorities, you’ll probably need as much ammunition as you can muster. It is vital that in prepping yourself to cross the final hurdle to secure funding, you don’t overlook the power in the human outcomes you plan to drive, be that better care, safer communities, or a cleaner environment.
Marry the two and you should have a winning formula.
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Richard Walker, Data and Insights Partner, Agilisys