Measurement as part of the solution not part of the problem
Measurement gives a subject respect. It provides focus and some feedback critical both to understand the past and have a thesis about the future. In investment, measurement is everywhere. ‘Figures don’t lie’ is the simple mantra. But are they telling truths? I have serious doubts.
We measure what we do because we can. The availability of certain measures, take investment performance, inevitably generates a healthy focus on the situation. But it cannot help our understanding without a lot of context. Past performance is neither an effective guide to the future or the past.
Accurate measurement does not equate to materiality or meaningfulness. This is because the investment system we are dealing with is very inter-connected and complex. So, correlations will be weak and there is no simple causation at work. Hard data takes us only part-way in our challenge.
The first response here is the need for ‘soft data’ in addition to the hard stuff. Soft data is information that maps indirectly and inexactly to the concept you are measuring using assessment, surveys or proxies. For example, process measures are valuable in investment as they map indirectly to performance. They are soft data. And while past performance does not imply good future performance, a combination of good performance and good process (as assessed, surveyed, or proxied) might do that.
The behavioural context to measurement is particularly important. There is one ever-present example here – how measures that are adopted as targets lose their effectiveness because of gaming. This is such a far-reaching principle it has an economic law describing it – Goodhart’s Law; and a slang term – ‘munchkining’ (derived from video games where players miss the point by focusing on the letter of the game rules over their spirit).
This gaming problem has worse outcomes when only one measure is the central target. With investing, the process of optimising return over risk has had its popular following but fails spectacularly in practice. And with companies, the focus on earnings per share fails by not managing ESG factors and the wider stakeholder issues. So how can we do better?
First, seek maximum alignment by being as clear as possible on goals. Here some goals may be measurable but wider framing in qualitative goals should play a big part too. Second, seek maximum feedback. We need more focus on the ways and means to achieve the goals and get feedback from the measures of process alongside the measures of performance. Third, seek balance in thinking and reporting. This calls for fully integrated thinking that places results in context.
Are there any tools that can make a big difference? I suggest that the balanced score-card, first advanced by Kaplan and Norton, is very useful to assess the performance results as much on quality terms as in a quantity. And I strongly support integrated reporting as the route that asset owners should be taking in their wider communications as Cbus the Australian fund exemplar has already demonstrated.
Strategic asset allocation and total portfolio approach
We have been high level and abstract above. My interest in this subject is concrete in one issue. This is a particularly important application in considering the SAA investment process (Strategic Asset Allocation). This approach is followed by most asset owners but it suffers considerably from all the measurement difficulties described above.
First, there is an alignment and gaming problem with investors managing by sectors and versus tracking error not by total fund and versus the total fund goals. Second, it has a feedback problem as the SAA even with a perfect start will be way short of optimal as conditions change. Third, there is a balance problem, with sustainability, liquidity, governance and complexity all under-emphasised.
A big change in investment process is surely coming here. THe alternative methodology – total portfolio approach (TPA) – is practiced as yet by only a handful of large asset owners. But they are leading a quiet revolution in investment strategy thinking and practice.
In TPA, the investment team coalesces and works on one shared objective, in SAA the team divides and works on their respective separate objectives
TPA is clearly capturing three key benefits: better alignment by replacing the SAA emphasis with fund goals, better feedback through performance quality scores, and more integrated thinking and reporting in the mix. This is setting asset owners up with, well, simply much better measurement and performance.
To bring this to life in an example, in the SAA the asset class team (think equities or liquid alternatives) has a natural incentive to spend their tracking error risk budget on beta (producing a higher information ratio), but in doing so produces a drag on the total fund by over-loading beta risk (producing a lower Sharpe ratio).
By contrast, the TPA is set up to integrate the beta and the alpha (one shared objective) and properly value uncorrelated alpha. It sets the measurement up free of explicit gaming. It is not simple to integrate in this way, but if it was simple everyone would be doing it. But this is simply better design of the process.
When Einstein said, ‘not everything that can be counted counts, and not everything that counts can be counted’, he was right. But what he should have added was ‘we can count much more and much better than we do’. And we do that by designing measurement to be part of the solution not part of the problem.