Asset management hiring practices are not keeping up with a changing world

In her latest column for Citywire, Phryne Williams looks at the challenges asset management firms face in hiring – and retaining – scarce, tech-focused skills.

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In 26 years of recruiting in the investment industry, I have never seen such a high volume of hiring as today. And, unfortunately, a lot of it could be done better.

Many processes are not keeping up with a fast-changing world. Hiring is up because retention is down. Younger generations are coming into the workplace with new, often scarce skills that businesses require, yet they are struggling to engage and retain them.

Workplace practices and culture have not adapted to effectively assimilate younger workers who have different motivations, different aspirations of work and different expectations of their leaders. Getting these things right within organisations is critical for any asset management firm which understands the value of their employer brand.

For asset management firms today, data scientists, machine learning specialists and quantitative analysts – particularly those with significant experience in credit, fixed income, currency and cross-asset quants – are amongst the most challenging candidates to find.

The search experience

Recently, one of our clients approached us to assist in finding a new team member with equity, fixed income and credit experience. It was a tough ask in the relatively small South African market where that skillset is particularly scarce. Rare talent like this is also usually well-looked after. We were therefore also facing the reality that if we could find the qualified candidate, it was likely that they would be happy, well remunerated and not open to a job change.

What also hinders a search such as this is that the client recruitment process is often drawn out and complex. It involves multiple stakeholders, busy diaries, and numerous hoops to jump through. This includes interventions such as psychometric testing and the feedback from it.

All these steps can extend processes to months. And then, at offer stage, the company has sometimes under-budgeted for the role.

In this particular case, we found a great match for our client, but the promising candidate lost interest during the onerous process and withdrew.

It was clear there needed to be a better way. With the client, we co-created a targeted, strategic interview process, leveraging technology. We extended our networking and search efforts to include offshore. Fortunately, through our network, we secured an offer for a candidate who was eager to return to South Africa.

However, the smartest outcome from this experience is that client then mandated us to deliver a market map so that we could build a talent pipeline for future hires. The client is now engaging informally with passive candidates in order to fast track their next search. Ultimately, this will result in being assured of a set of pre-screened candidates setting them on track for a short, swift recruitment process in future.

Oversight and mentorship

This illustrates how finding new skills, especially tech-related ones, throws up new retention challenges for asset managers. We have clients hiring for new artificial intelligence (AI) and machine learning (ML) roles, who, quite understandably, don’t really know what their new team member is actually going to be doing. They can’t provide quality oversight, advice and mentorship themselves.

Companies currently building AI and ML into the fabric of their organisations need to embrace a range of critical success factors. These should include a well-communicated vision of a data-driven firm and a supportive change management process that helps techies assimilate into the workplace. This will promote the necessary communication processes to bridge the gap of understanding between techies and other team members.

Without this, frustrations abound on all sides. Time, patience and intentional effort are necessary for the organisation to work together towards the shared vision of what the future data-driven business will be like.

Outside mentors who can provide oversight may be a necessary investment for managers who find themselves trying to oversee, inspire and advise team members doing jobs that the managers don’t fully understand. Despite a small playing field in markets such as South Africa, many firms have global partnerships and associations that they can leverage to find mentors and expose employees to global best practice.

In addition, executive coaching can help business heads to define goals, identify roadblocks and brainstorm solutions. Bringing new skills into the asset management means new processes and new solutions need to emerge.

It would be interesting to hear from readers – do you recognise these challenges? And, if so, what’s working for you? 

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