Top performers are an elite group who, at the start of their tenure, typically outperform laggard colleagues by a multiple of three; rising to five times at their peak, before dropping back to a multiple of only two to three in later years (Figure 1).

The solution to this mid-life dip lies in improving our understanding what motivates and engages these top performers at the beginning, and sustaining that in later years.

Figure 1: RM Performance by Tenure


Increasingly, the more progressive private banks are applying people data science to improve business performance of their front office, often to the tune of millions of pounds.

By analysing RM pay and productivity within the market context and identifying where their RMs sit in a simple pay versus productivity matrix, firms are able to identify cost savings and revenue enhancements. In short, RMs sitting above the corridor of efficiency have cost: income (C:I) ratios that are simply not sustainable over the long term (see Figure 2).

Figure 2: The Pay vs. Productivity Matrix1

1 A Pay vs. Productivity Matrix shows how a firm’s RMs are plotted against a percentile rank of the whole market, both for their pay (defined as total compensation of salary plus bonus) and productivity (defined as total revenue generated per RM). The dotted lines define the zone, a corridor of efficiency, where productivity and compensation rank are most closely aligned – an ideal situation. Points outside of these lines suggest that the business is inefficiently rewarding their RMs relative to their productivity. The graph is further split into four performance quadrants; the top left high pay, low productivity quadrant offering specific opportunities to either reduce costs by reducing pay in line with the market or increase revenue in line with the market.  


To date firms have struggled to apply objective learnings from their top performers, struggling to bottle what makes them so successful, let alone administer the secret potion to their other bankers.

But, times are a changing. The recent emergence of more sophisticated artificial intelligence profiling tools such as ADEPT-15TM2 is now enabling firms to create a true DNA blueprint unique to their top performers’ behavioural success traits.

Borne out of technology used by the U.S. military, assessments can dynamically adapt questions asked of candidates to stop them from gaming what the right answers should be for a particular role. This adaptive, AI aspect is vital to create a true profile of an individual’s behavioural traits.

When we link these profiles to business results, such as client experience, productivity, and conduct, we see that another commonly accepted adage is holding true – it’s not just what you do, it’s about how you do it that makes the difference.

Despite many firms diligently distilling best practice into manuals of what a RM should do, evidence suggests that it is an individual’s behavioural traits – the how – that really make the difference between being a top performer or not.

Of course, these success traits vary not only by role, such as a RM versus a product specialist versus support functions, but also by firm culture. So what may make an RM successful at one firm, can be subtly, but critically, different at another.

In fact, firms applying this science to their talent selection are already seeing dramatic improvements –increasing the chance of recruiting a top performer by a factor of 200-300%! This new wave of people science is increasingly being used across all elements of the talent lifecycle to make more effective hiring decisions, design more impactful development curriculum, reduce conduct risks, and improve engagement and the client experience.

Some are applying these learnings to enhance the development curriculum for under performers; others are taking it a step further to identify RMs that won’t make the grade in order to free up investment and resources for those that will.

By better understanding the behavioural traits and engagement drivers of RMs, not only can we help learn what makes them special, but also sustain their motivation after their mid-life dip. Benefits for the firms grasping this new opportunity are not only obvious, but very significant.

The bottom line is that applying people science and leveraging smart data and insight across the talent lifecycle is already seeing dramatic improvements in the effectiveness of firms’ human capital and business performance metrics.

Even in this age of digitalisation, people are still a firm’s biggest cost, and also their greatest asset. It’s therefore maybe unsurprising that delivering better business performance through better people performance has risen to the top of many CEOs’ agendas and looks destined to stay there for a good while to come. Maybe there is more to be learned from top performers.

* This article has been adapted from an earlier piece written by Mark.

Cover photo from kjarrett, used under creative commons license.

News from the world of wealth:

OCBC Bank pilots robo-advisory service – Hubbis

Bank of England sets up fintech community; runs blockchain and AI trials – FinExtra

Key themes to explore with your money manager – FT Wealth

UBS spending USD1 billion in IT overhaul – Reuters

Schwab adds human touch to automated investment service – FinExtra

Thought of the week:

“Science is not only a disciple of reason but, also, one of romance and passion.” – Stephen Hawking

MarkAuthor: Mark Miles, Associate Partner, European Wealth Management.

Expertise: Mark Miles leads McLagan’s Wealth Management & Private Banking practice in Europe, responsible for the development and delivery of market leading business performance consulting.

Background: Mark has over twenty years of consulting and industry experience in financial services, centred on the private banking and wealth management sector. Mark holds a Masters (MEng) in the Manufacturing Engineering Tripos (MET) from St John’s College, Cambridge University, and completed an Accelerated Development Programme at London Business School.

Leave a Comment