Let me be blunt: If you have been writing your strategic plan in the past five years without a big red warning light flashing on regulatory change as a disruptor/key risk to your business, then you have been in denial.
If the regulatory environment hasn’t been flashing at you as a driver to innovate, and potentially rethink your business model, then you have been asleep.
There are market forces amassing outside your business that are either a positive or negative, depending on your attitude. Change and the threat of imminent change affect us all. The new, post-Future of Financial Advice world demands a new regime, new remuneration models and new expectations from consumers.
See beyond the techno-threat
Much is made of so-called digital disruption, robo-advice, fintech, machine learning and cloud-based solutions; raising fears of some in-built redundancy in what we do as a profession. The reality is that change has been around in business since long before computer chips were invented. However, anyone thinking their business will improve in profit or increase in value simply by doing the same things and buying more technology is missing the point. Clients may accept e-advice but will draw the line at an e-adviser.
Let’s just, for one moment, take the ‘digital’ out of digital disruption of a business model. Let’s instead focus on the life cycle of a professional practice, and the part of that cycle in which a business is most vulnerable.
When we first start out in practice, it’s all about learning. We are learning what works, what doesn’t, what we will do differently to separate ourselves from others. In this stage, we cope with this uncertainty because we are willing to experiment, we are agile. We are all about learning in the now and working towards creating value based on the expectation of future earnings. We are willing to accept volatility in earnings, because we see this experimentation as an investment in the future of the firm.
We then reach critical mass, employ staff, and need to manage things; we start to lock in policies, routines and processes. We are taught that the job of management is to iron out process variability and lock in standardisation. We see this in practice through the introduction of quality processes – electronic working papers, standardisation of advice documents. We see it in HR policies, in style guides for marketing, even how we answer a phone call.
But as we try to standardise everything, to write procedures and policies, things become more complex. However, we are trained that standardisation is how we build a leverage model in professional practice. With a leverage model comes value generation through having others “on the tools”.
We strive for efficiency and we look for steady results. The measure of success is now delivery of consistent but growing cash flow. As the leader of a large firm, I know the grind that comes with continually increasing performance expectations, thinking only of consistent earnings growth. The pressure from partners is about steady earnings, so they can meet personal obligations like loans, school fees – the usual stuff of success. The default position of management decisions is now simply, “How much will that cost?”
Know when you’re vulnerable to disruption
I think we are most vulnerable to disruption when focusing on consistent growth in earnings becomes a perceived strength.
What tends to happen is a new business model comes along, and we don’t see it at first because it isn’t profitable yet.
A recent example for financial planning was firms moving away from commissions to fees. Initially it wasn’t profitable. Practices weren’t being rewarded with overseas conferences or dealer group awards; they weren’t winning Adviser of the Year in the trade press.
But what people didn’t realise was that it wasn’t all about moving away from commissions. The new business model was planners moving away from having to sell financial products to get paid. It was centred on giving financial advice and putting our clients’ best interest at the heart of our business model.
This was the start of the separation between the product distribution model and the advice model. Look at what has happened since; fee-for-service is validated and profitable.
Define what you are (and aren’t)
The question to ask is, “What is our real role?”
If you’re holding yourself out as an asset manager, you run the risk of management questioning this business model. You are in competition with some smart algorithms and the power that comes with artificial intelligence and machine learning.
Your firm’s management group has an existing revenue stream to protect. They are far more comfortable developing a strategy for a business they know how to operate, and are reluctant to enter a new game with rules they don’t understand. When one’s job is to protect the core, one loses sight of the fact that the new entrant with the new model has only upside to capture.
It will take leadership to convince the big revenue generators in your practice to give up some of their domain and their resources to potentially invest in something unproven.
With the goals-based advice model, however, leaders will filter out this noise and see the growing movement. They will invest resources in helping clients set goals, track progress against these goals and recalibrate as circumstances change.
The innovation coming to enable this movement is real-time data from multiple sources, all linked to one firm application. Real-time, detail-rich data will validate your strategies for reaching your clients’ goals.
In short, leaders will understand that data in financial planning – alongside so-called disruptive forces – is the new oil!
Matthew Rowe is an independent director, a business founder and owner, and former chairman of the Financial Planning Association of Australia.
Author’s acknowledgement: A number of points in this report originated in the article, “An Incumbent’s Guide to Digital Disruption” by Chris Bradley and Clayton O’Toole, from McKinsey Quarterly, May 2016.
TOPICS: business models, data, digital disruption, fintech, goals-based advice, machine learning
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