David Werdiger is the managing director of the private family office Nathanson Pearson in Melbourne, Australia, and the author of Transition, a book on preparing for wealth transfer. Werdiger spoke with Crain Currency about how he works with high-net-worth families and on planning for succession.
Can you tell us about your background? What led you to work with high-net-worth families?
It really started with having grown up as the youngest child in a HNW business family and one very involved in community. I worked in the family business as a child and as a student and felt quite self-conscious, as the boss’s son, about how others might perceive me. By the time I finished university, I decided not to join the family business. Three other family members all 10-plus years older than me were already working there, and I didn’t see a place for myself. I had a job for a few years but always wanted to be in business because that’s what I saw growing up.
Through 20-plus years of my “second career” as a tech entrepreneur and through several nonprofit directorships, I learned a lot about governance, strategy, intergenerational issues, philanthropy and family offices. I got to know a number of other families and heard their stories. I observed up close what no-profits and families did well and the huge cost to them when things don’t go well. This fed my passion for good governance — what I essentially describe as the responsible use of power.
After completing a master's of entrepreneurship and innovation, I found myself writing and speaking about family wealth. I was thinking about what I wanted to do with my life — aware that in my own family, there would be an intergenerational wealth transition. I had already learned a lot but needed to continue that and to prepare myself for that future. At that stage, I decided I wanted to help other families on their journey, so I wrote a book and became a family enterprise adviser. That was the beginning of what has become my “third career,” and it has been developing nicely over the past few years.
How would you describe your approach to working with clients?
Holistic. I serve the whole family rather than any one family member. And when working with an individual, I work with their entire self: business, personal and the integration of all parts of themselves. I’m very top-down, pulling back to the big picture and then working down from there. That means there’s initially a focus on values and purpose, and everything either flows from that or has some connection to it.
It’s easier to answer questions like “Why are we doing X?” when we can link them back to the family’s or individual’s values.
Another big area of focus for me is process and decision-making. My goal is to help families make good decisions together. That means families need a good decision-making process — one that raises all voices, considers decisions within the broader family context and therefore generally leads to better-quality decisions. These principles apply equally to my work with family groups and also entrepreneurs and family businesses.
You wrote a book, Transition, about preparing family businesses for wealth transfer. What do you think are some of the most important steps family businesses can take today to prepare for the inevitable changes they will face in the future?
Firstly, be open to change. Not every family business is meant to last forever. The ones that last do regular strategic planning, are prepared to reinvent themselves, make significant changes to the way they do business and avoid holding “sacred cows.”
Secondly, ensure the family members involved are there because they want to be. In families, there can often be an implied or actual obligation to join the family business. When this happens, it can lead to resentment and a sense of being trapped. Being part of the family business isn’t for everyone, and having clear policies on how family members are prepared and qualified to join leads to them being more engaged and aligned.
Finally, provide a pathway for incumbent family members to move to the next stage of their lives. Note: I didn’t use the “r-word” [“retirement”] for a reason. It has connotations of being moved out to pasture and no longer being of value. In a family enterprise, it’s the opposite. More senior family members are a huge source of social capital in the family. So, it’s about helping them transition to the role of “elder,” where they can support/guide/mentor others rather than remain operationally focused until the day they die.
You are writing a second book, focusing on social media. How do you think the constant connection to the digital world has impacted succession planning?
That’s a fascinating question. I actually wrote an earlier version of that book before I wrote Transition, then put that project on hold. I have wondered about the link between the ideas in the book and the work I do with families. The constant connection to digital is, among many other things, another manifestation of the generation gap, which has existed for centuries. Parents and children often live in different worlds and talk different languages. The bigger impact of the digital revolution on succession planning is how it has disrupted so many businesses — that is probably a more significant threat to family business continuity.
What are some of the common succession challenges that you help your clients work through?
Family business succession can be a tricky one. There is the “sticky baton.” The incumbent who says they want to retire but don’t really. So they talk about it and talk about it but never push the button or agree to a formal plan. Or — and this can sometimes be worse — retire but don’t really let go and remain involved.
Then, there is the situation where none of the children want to join the family business. And the reverse, when children are in the business and aspire to move into a leadership role but don’t have the capability.
Another big challenge is when there is an existing conflict situation, sometimes between the incumbent and the rising generation over key business decisions, or within the rising generation over roles within the business or distribution policies or … well, anything.
How can family members develop productive and open ways to discuss and overcome these challenges?
The way to overcome these challenges is largely through discussion. The problem is that just the relevant family members sitting down around a table and trying to work things out often doesn’t work. There are a few reasons for this. One is that there is far more around the table than just the family members. There is the implicit family hierarchy and power dynamic, which means parents will act like parents rather than business owners or partners. Birth order and gender stereotypes can also be an impediment to hearing voices on their merits. I know this from experience — I’m the youngest — and from families I’ve worked with.
Then there are the decades of emotions and family baggage. A conflict that is expressed as who should be CEO might actually be a proxy for a sibling rivalry that started when the siblings were children and remains unresolved. The real issue is often beneath the surface, the things people don’t like talking about.
That is where having a genuinely independent voice around the table can help facilitate open discussion, confront the actual problems and reach consensus. The discussions can be very difficult, but that’s not a reason to push them off. In fact, it’s the reverse. Issues often fester and grow the longer we delay dealing with them. Part of that process is developing a set of guidelines — they might be called a code of conduct or a family charter — which determine the rules by which the family operates. These are all the tools of good governance, and they apply equally to families as they do to organizations.
Interview conducted by Carrie Pallardy
Let artificial intelligence manage investment risk
By JULIA BONAFEDE
The public debate over artificial intelligence, focused on its risks and benefits, tends to overhype both extremes. There is a public perception that AI algorithms can self-automate and make decisions apart from or at the same caliber as their human creators, a process more widely known as artificial general intelligence. Without a mechanism built by a human, this perception is not accurate.
The use of advanced AI is growing exponentially beyond our comfort levels of convenience and daily utility, triggering valid fears of less human control. Responsible human oversight — paired with consistency and reliability of AI models and administered through a lens of common sense, strong ethics and fairness — will manage the conversion of fear into trust. Implementation must have quality and bias controls firmly established as part of human oversight.
For investors to relinquish human control of their investment decisions and rely more on AI, trust and track record must serve as proof. At Rosetta Analytics AI, our eight years of development and deployment of neural-network-based investment strategies shapes our views of the rewards and pitfalls of harnessing the relationship and risk allocation power of deep reinforcement learning. We, collectively, believe that now is the moment to convert fear into trust.
First conceived in the late 1950s, neural networks are algorithms coded to search for sequences or relationships that exist in data. They have surpassed the human brain’s capability to solve certain problems. These algorithms are quite proficient at performing clearly defined tasks, such as predicting the next sentence in a paragraph based on previous word sequences. They filter noise from data more efficiently and more accurately to calculate a prediction or an output than more linear or cluster-based statistical frameworks.
Computer science — democratized by the advent of server clouds and combined with the acceptance of open-source code and code repositories — has exploded the universe with ideas to make mankind “better than he was before. Better. Stronger. Faster." Unfortunately for investors, the investment industry has been slow to adopt this technology.
The characterization of autonomous algorithms is largely negative as portrayed in various novels like Flash Boys. Public mistrust of AI is a natural consequence of high-frequency trading firms physically moving themselves closer to exchanges to obtain an information advantage by accelerating the timing of data they extract from data pipes using autonomous predictive algorithms. A recent example of rogue traders overriding models undermines perception and trust even more.
Now the market is excited by the rapid release of next-generation deep reinforcement learning-based large language models (LLMs) like ChatGPT, Bard [now Gemini], Claude, et al. These are just some of the advancements taking place in advanced artificial intelligence. Debates over issues like copyright infringement are finally spurring meaningful conversations over who has rights to the data and other issues surrounding data privacy. These developments are healthy to increase public trust in the responsible use of this technology.
Market excitement about AI should go beyond natural language processing. The use of neural networks like deep learning, combined with the development of optimization frameworks like reinforcement learning working in concert with neural networks, is revolutionizing the ability for a quantitative framework to extract information from data. These systems simultaneously make a decision that incorporates both sequential and cumulative behavior in data to determine how to allocate portfolio risk.
We believe there is investment alpha to be earned, even in public market data. Since no two models are alike, investors have an opportunity to be rewarded by conducting careful due diligence on investment firms deploying AI directly into the investment process. Instead of pursuing investment alpha, many investment managers seek to maximize operational alpha by focusing their investment in AI on the back office and trade execution to squeeze more costs out of their book.
The expertise required to create, deploy and monitor AI-driven allocation models requires a specification, compliance and governance process that should already be in place for all quantitative models. Allocators historically did not have the resources to evaluate the design and implementation, whether simple common factor models or more opaque models like neural networks. The integration of investment teams with both computer science and financial expertise is solving this knowledge gap.
Dynamically extracting relevant information directly from data, learning from these changes in the underlying market environment from which the data is being extracted, and simultaneously learning to allocate risk is a game changer. Consistency of results and direct experience gained by their human creators is the catalyst that will drive acceptance by turning fear into trust.
Julia Bonafede is the CFA, co-founder and CIO of Rosetta Analytics AI, where she has focused on research and development of the firm's investment platform. Before co-founding Rosetta Analytics, Julia spent 24 years building teams and offices at Wilshire Associates.