The data dilemma: do you play offense or defence?

Superfund data dilemma: When it all goes wrong
July 31, 2018
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August 2, 2018


By Mark Vaughan

The phrase “Offense sells tickets, but defence wins championships” has been used by many great coaches across the sporting landscape.

In recent times, this concept has spread from the sporting field into the white-collar world.

The idea of offensive versus defensive data strategies was brilliantly outlined in the DalleMule and Davenport ‘What’s Your Data Strategy’ piece in the Harvard Business Review.

While the concept has been widely discussed in the international data management community, it’s yet to gain much traction in the Australian superannuation vernacular.

Offensive versus defensive data strategies

The term data strategy sounds like a combination of the two most overused buzzwords of 21st century business.

But super funds at the forefront of strategic thinking understand the importance of having one. While data offense and data defence are relatively new concepts, the prevalence of big data, greater focus on governance (think Royal and Productivity Commissions) and the transition toward data ownership (think Open Banking) have made a data strategy central to successfully managing a super fund.

Let’s first understand the terms:

Data offense focuses on using data to grow your fund, investing in activities that aim to attract new members and increase member satisfaction.

Data defence is about minimising downside risk. This can include solving data problems, neutralising data threats as well as complying with regulatory requirements.

While most funds have both data offense and data defence as priorities, the past five years has seen a significant pendulum shift toward data offense within the super industry. After years of focusing on regulatory and compliance reporting, funds have pivoted toward a more offensive use of data focused on analytics and member-facing digital solutions.

This has been driven by an increased competitive landscape and greater emphasis on having an understanding of, and connection with, the member.

But has the shift gone too far? While the volume, use and value of data has continued to rise, the poor quality of data can act as a handbrake to the success of offensive efforts. For example, having a robo-call that wishes a member a pre-retirement ‘happy 65th birthday’ is counter-productive if the member is actually 34 and it’s not their birthday.

What’s more, in the super industry, these robo-calls would have had a meltdown on 1 January 2015, as 1 January 1950 is by far the most common date of birth held by super funds. This is not the result of some anomaly in baby-boomer birthdays, but a data integrity issue where a default date is often recorded where the information is missing from the relevant application form.

While the offensive robo-call strategy has merit through engagement and customer satisfaction, it can come undone if the defensive strategy has weaknesses.

There is an inherent link between the two. A well organised data defence strategy can empower your offensive efforts. If data is accurate, secure and available then it is far easier to exploit. If it’s defective and disparate then your offensive efforts will come undone.

Data return on investment (ROI)

Perhaps key to the offensive pendulum shift lies in the difficulty of measuring the ROI on defensive data strategies.

Activities such as data quality controls have a less tangible ROI. A data integrity validation that prevented a unit pricing error from spreading across the entire membership can literally save a fund millions of dollars. However, the savings are compensation costs that were prevented and reputational damage that was saved, so attempting to quantify these is both challenging and subjective.

While not necessarily measured, the defensive and offensive efforts often compete for finite resources, funding, and people. When an executive is seeking budgets, it’s natural to focus on what is considered more positive and visible offensive efforts. Their KPIs are generally geared toward growing the fund, and a strong focus on data offense allows for that.

However, the quality of data is the heartbeat of any organisation’s data management efforts. If your data is not managed correctly and quality is not ensured, your data can quickly become a risky and expensive liability instead of a valuable asset.

The source of the truth

Central to a data strategy is how you store and manage data; remembering that every business unit requires access to accurate and available data.

In theory, a defensive strategy has a single source of truth (SSOT), while an offensive strategy has multiple versions of truth (MVOT). To strike the right balance, you need to create an operating environment in which data is both tightly controlled and flexibly used.

In the current political climate, the idea of having multiple versions of the truth doesn’t sound too appealing. What funds should be looking to achieve is having multiple sources of truth supporting a single version of the truth.

Unfortunately, this is a rarity across most large organisations, super funds included. You’ll often read that data has become the most valuable asset in the world. And all super funds are data-rich these days. And yet, in the so-called data revolution, they’ve become information-poor.

In the absence of a comprehensive and well-managed data strategy, each business unit or project team has gone it alone in developing customised data solutions focused on immediate needs. This has resulted in an increase in multiple versions of truth (MVOT), leading to gaps, overlap and inefficiency. Hence you end up with the flexibility of data availability but without the control of data accuracy.

Frequently fund executives are baffled; they’re looking at two reports listing the number of members within their fund and both have completely different results. The causes are varied, but generally the result of MVOT and the inability to access accurate and available data.

Finding the right balance for you fund

So how do you find the balance between offense promoting flexibility and growth versus defence requiring control in your approach to data?

The Harvard Business Review piece succinctly states that information is data with relevance and purpose. Here are a few key initiatives that can give you the chance to realise the true value of your data and transform it into information:

Develop a data strategy: don’t feel embarrassed if your fund doesn’t have one, you’re not alone. But remember that if you don’t have a clear data strategy, you are in fact already paying for one. The strategy is disjointed, reactive and often hidden – but it does exist.

Measure return on investment (ROI): put simply, you cannot manage what you do not measure. Develop a series of metrics focused on that matter most to the business – these will provide a factual basis on which to justify, focus and monitor your offensive and defensive efforts.

Don’t confuse defence with negativity: while it’s natural to focus on what is considered more positive and visible offensive efforts, the accuracy of data can will often determine if these efforts sink or swim.

Invest in your data: taking a dollar out of an operations budget to put into a marketing budget is not the answer. It’s like the road versus rail dilemma that is the groundhog day of political debates. Your data is an asset and you need to invest in it accordingly.

Back to the phrase “Offense sells tickets, but defence wins championships”; in the current competitive landscape, you don’t have the luxury of choosing one over the other. Super funds that want to thrive will need to successfully navigate through the need for both.

Mark Vaughan is managing director at QMV.



First published in: SuperFunds Magazine August 2018