Pensions and benefits have always constituted a significant spend above the cost of employment and the size of that spend has steadily increased in accordance with rising expectations. Across the board, we’re seeing greater emphasis on later-life security and a paternalistic tendency amongst responsible employers.

However, this long-term development has now been compounded by a sudden – and, in some ways, irreversible – crisis whose devastating impact on the global economy is forcing every employer to examine costs more carefully.

Thus, pensions and benefits have been driven to the centre of a new, more strategic mode of corporate decision-making. Now, more than ever, there’s a two-tiered challenge facing pensions managers: to purge their schemes of excess spending (and thereby compensate for any fall in revenues) whilst also protecting member outcomes by increasing the value of the spend that remains.

In both these respects, access to agile and intelligent data sets will prove essential for success.

Here are some examples of how multinationals can use the wealth of information made available by pensions tech to undertake a more strategic conversation on their various schemes. In so doing, they can reconsider their deployment of resources, the distribution of their costs and, ultimately, how those costs can be reduced while maintaining – or improving – the size and quality of member outcomes.

Reconfiguring your cost footprint
The ability to access millions of real-time global data points through a simple and centralised pensions analytics tool is helping trustees understand the distribution of their spending and, in turn, challenge what’s acceptable.

In some cases, this could mean consolidating schemes and centralising costs as much as possible – perhaps by converting your existing mixture of DC and legacy DB schemes into a single DC arrangement, or by working with a master trust to reduce your reliance on third-party administrators.

In others, it could mean identifying regions where your schemes are over- or under-performing and working to make them both more beneficial and more cost-efficient. Member outcome modelling, combined with comparisons to local norms, allows a multinational to gauge its offerings against its competitors’. Then, once an inefficiency has been identified, contextual information shows how best to address it.

For example, you may be paying higher pensions than your rivals in that sector, but what workers in that region really want is better healthcare. In this way, you can adjust your wider benefits packages to better cater to employee needs – and to ensure that you’re only paying for what matters most, where it matters most.

Negotiating lower asset management fees
Even if consolidation isn’t your solution, a global pool of pensions data is still a supremely powerful weapon in the battle to reduce unnecessary costs, for it can also be used to challenge pricing directly.

Sometimes, for instance, a single firm is paying the same asset manager different fees in different regions – often to facilitate a similar (and relatively straightforward) investment strategy, such as index tracking. Focusing on static data sets for any one region could leave this simple yet empowering fact uncovered for years and prevent you from bartering for better fees. But a broader, more holistic view of costs and charges equips you with a benchmark and a basis for discussion.

What is more, it might also confirm your bargaining power. It’s easy to assume that the biggest clients pay the smallest fees, but this is seldom the case because those clients rarely realise how much weight they carry. Holding several schemes with a single manager makes any multinational a major entity worth retaining – even if that does mean conceding a couple of basis points.

How exactly that saving presents itself will of course depend upon the schemes in question: in a DB arrangement, the money is returned to the scheme itself; in DC the saving directly improves members’ long-term outcomes and reduces the need for supplementary provisions in the wider employee benefits package. Either way, a wealth of global data is the key to unlocking your negotiating power and the grounds on which to base your new objectives.

Reproducing your own successes
So far, we’ve seen how external factors such as local context, consciousness of one’s competitors and careful management of third-party fees can make your pension schemes more cost effective. But there are gains to be made by looking inwards, too.

Side-by-side analysis of any company’s own provisions will reveal successes that can then be repeated in other regions. And the greater the number and variety of data points, the easier it is to determine best practice.

Let’s suppose that Schemes A and B in France and Germany are outperforming Scheme C in the United States. What might once have called for a colossal, cross-country feat of administration can now be solved by a slick, centralised comparison of regional data to identify the differences affecting those results. Perhaps it’s a question of investment choices, or perhaps your provider in Chicago is significantly more expensive than their counterpart in Stuttgart. Whatever the issue, an intuitive tool for interpreting data can turn a regional success into a global template.

In this way, innovations in pensions technology are not only redefining what we recognise as ‘good value’; they are helping companies protect their past achievements from today’s uncertainty and maximise their workers’ prospects for the better times to come.