With all that’s happening in the world, the ability to use data to make smart decisions is key, says Adam Jones, chief technology officer at U.K.-based consulting firm Redington.
While the importance of data has gained new significance amid the coronavirus pandemic, Redington built a financial technology tool before the crisis called ADA Research, which plan sponsors can use to access data and drive decision-making.
The tool was originally developed in-house to help Redington’s investment research team with day-to-day business. “That was the genesis of the tool,” says Jones. “But really the tool became quite quickly a very flexible data platform.”
Ford Motor Co. was the first global plan sponsor to use the tool starting in December 2019. Redington started working with the company to understand the challenges it faced as a multinational with a big pension and benefits team. “What we found was that one of the big issues was availability of data, accuracy of data and then being able to pull together the data that they did have to make more meaningful decisions to help drive strategic thinking.”
In the case of Ford, it has a central global team based in the U.S. and then regional pension and benefits teams. But it operates with a global budget it must allocate across multiple countries. “There’s a real challenge in trying to understand how that money is split down between those countries and then ultimately what value does that drive for the end member,” says Jones.
For example, it would be difficult to understand whether a Ford employee in South Africa is paid well from a benefits point of view compared to other employees in South Africa, he notes. “It’s also hard for anyone who’s working in the global function to really get a handle on what local information means to them.”
Redington’s tool also helps to support Ford’s requirement for data. “One of the big things the platform does is it tries to solve that problem by making the data available by putting ownership in the hands of local [human resources] teams to be able to keep the data up to date, but also then aggregating that up to the global team so that they can start to make smarter decisions around that spend,” says Jones.
Generally speaking, the tool can help plan sponsors assess how they value their benefits provisions in a certain geography, he adds. “Depending on what country you’re in, there will be some level of state pension provision, typically. There will then be the employee pension or the employer pension contribution, but you’ll also have things like health benefits, dental cover, life insurance, etc. And in some countries the pension provision isn’t actually the primary concern of local workers because they don’t have health care, for example.”
In that case, an employer would be able to determine whether it should be investing more in health care instead of pensions or weighting investments toward health care to get better retention in the workforce and provide more value to employees in that country. “It’s really hard to make those decisions if you don’t actually have access to that data,” says Jones.
The tool also breaks down third-party cost data. “Quite a nice example that we have worked through with a client was how much are asset managers charging them versus how much are they charging their peers, because obviously as a big pension scheme you’ve got pretty big negotiating power, right? But in order to make the most of that negotiating power, you actually need data to understand, and while some people may think they’re getting a great deal, maybe they’re not at all depending on what they’ve got.”
Of course, data is a big challenge for pension plan sponsors. “As an industry, globally, it’s a real challenge because the pensions industry is old and a lot of the technology that exists within it is legacy and pretty dated,” he says. “Being able to get a hold of that data is a real challenge.”
Instead of assuming the system can acquire accurate data for everything, Redington’s tool will input data and score it for accuracy. “Essentially, for any country or any scheme in the platform, not only do we get a feel for how many employees there are, how many assets there are, etc., but we also get a score that says whether we should trust that data. And, if you’ve got a very high data accuracy score, that’s great, you can start to use the platform to make decisions immediately.”
On the flipside, notes Jones, areas that show up with low data accuracy can be flagged for investigation and updating blanks before use for decision-making.