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The struggling outsourcer Interserve finally called in the administrators. Unlike Carillion, the demise of the firm has been orderly and public contracts have been protected whilst the firm's lenders arrange for a sale of the firm.
The failure has raised a question about public contracting and whether it is meeting the needs of citizens. Since the demise of Carillion it has been common to hear people ask, "how do you fix public contracting?"
It is important to gain some perspective at this point. Most contracting is successful. Buyers work hard to make the right decisions to protect public money and to deliver a service in the best way possible. It is those buyers that keep our roads functioning, our waste collected, our forces armed and our hospitals equipped.
When things do go wrong, they go wrong in a way that invites mockery: eye-watering numbers, ferry companies without ferries, buildings without working services, fantasy budgets and smiling consultants. (No public contracting scandal is complete without a full set of smiling consultants).
If there is a single problem with procurement it is that we're not good enough at identifying the problems that occurred, and then diagnosing how to prevent the problem in the future. The real problem is that we simply don't know when public contracts go wrong a lot of the time, or whether they were value for money. In fact, we often don't know where the contracts are in the first place.
There is a huge opportunity being wasted here. With good information on our public contracting, we could do so much more to understand what works. Data analytics allows us to do so much more.
What if you could predict that a tender with certain attributes will reduce the number of bids and drive up the price of your tender? What if you could know that a given supplier routinely exceeded budgets by 10%? What if you could spot fraud and collusion more easily?
All of this is possible today, if we had good data. But we simply don't know enough about where the contracts are, exactly who won those contracts and whether the contract delivered on-time and on-budget. It doesn't matter what you wish to focus on, perhaps it is driving more contracts to small business, if you set up a system to measure the inputs and outcomes from procurements, you can determine what works and what does not.
So instead of implementing big, far-reaching policies that seem to fail, we can use the data to get into the weeds and make the changes buyer by buyer, supplier by supplier, tender by tender. The UK public sector spends £840bn per annum on contracting, but we have little evidence that demonstrates how successful that contracting is. Our own eyes tell us that works, but with data we could do so much more.
There's a fantastic opportunity to use data to isolate and predict what will deliver the very best outcomes. The film Moneyball portrayed the use of statistical analysis to create advantage in professional baseball, its time to do the same for our procurement. Diagnose the problems, implement the fixes, rinse and repeat.