PROJECT
Turning round an investment company in trouble
PRACTITIONER
Kim Warren, Strategy Dynamics Ltd.
APPROX DATE
Summer 2019.
SITUATION AND CONTEXT
A large company providing pensions and other investment products to high-net-worth individuals had grown strongly during some years of good economic and stock market conditions. However, an economic downturn and collapse of global markets had seen its investment returns dive, and the business was generating serious and worsening losses. The company was contemplating the usual responses to such crises – cutting all budgets by 20%, canning a key upgrade to IT systems for customer/broker support, and banning 1st-class travel.
THE SYSTEM OF INTEREST
The investment business model is a variant of a more generic business system. Investors had been attracted, and rising revenue generated, by the range and appeal of its investment product range. Those customers were won by larger numbers of intermediary financial advisors. To generate more appealing products, the company had strongly expanded the range of stocks it invested in. It had hired many more investment managers and analysts to manage those stocks and funds, and large numbers of customer-facing staff to manage the brokers and investors.
APPROACH TAKEN
The CEO wanted all of the more senior staff to be involved in finding the solution, so set up a 2-day workshop to create a shared understanding of the problem and figure out a solution. To achieve this, the workshop deployed the strategy dynamics business model method, grounded in rigorous system dynamics principles.
MODELS AND INSIGHTS DEVELOPED
As the system structure was built out on the whiteboard, it became clear that, while the company’s resources had grown in quantity, their “quality” was badly degraded – new funds were being take up by fewer investors, new investors had less capital to invest and were being won by smaller brokers. The growing number of analysts and fund managers could not keep up with the expanding range of investments and funds, so the company’s investment performance fell. Small system dynamics models, using limited time-series data on the quantity and quality of the key resources, made clear the nature, scale and speed-of-change of the problem. They also indicated its likely trajectory, and the scale of responses needed for a strategic plan to rescue the business
KEY INTERVENTIONS
It was clear that the planned cost-saving campaign would do nothing to fix the basic problem. Instead, the team realised that they needed to “prune” all the weak, poor quality parts of the system. Smaller brokers were closed down, and smaller investors invited to consolidate their investments into fewer, simpler products. Underperforming funds were closed or sold off to other providers, which allowed the range of stocks and bonds to be rationalised. Fewer fund managers and analysts were needed, and the IT upgrade improved the productivity of customer support.
RESULTS
Within 6 months, the business was substantially smaller, but of higher quality – profitable again, and capable of growing once more, but carefully this time!
AFTERTHOUGHTS & OTHER POSSIBLE METHODS
In some ways, this group was easy to deal with – all highly numerate and comfortable with the whole idea of using ‘models’ to work things out. They might have gone along with more qualitative interventions, such as using feedback systems thinking to generate causal-loop diagrams of their system. However, while that may have clarified the nature of their challenge, it would not have made clear its scale or pace of change. Nor would it have shown them the scale and coordination of responses needed to rescue the business from disaster.
