Bart Balocki on Practices of Venture Capitalists
Or, how “big bets” are made on “incomplete data”. Bart Balocki, an alumnus of Stanford University, researched the practices of Silicon Valley (US) venture capitalists. These are rough highlights from his talk to the Edinburgh Entrepreneurship Club/Edinburgh-Stanford Link gathering on 17 October 2007. Bart covered the history of US venture capital, outlined how venture capitalists operate, and developed a model of how perceptions of value change over time.
Brief History of US Venture Capital
A simplified time-line:
- Prior to 1946, high-risk investing was done informally by wealthy families.
- Post-war, government led the commercialisation of new technology.
- In 1957 DEC (Digital Equipment Company) was successfully developed using a venture capital model. This was probably the first evidence that venture capitalists could earn a return. Other successes followed during the 1960s, notably Intel.
- In the 1970s Federal regulations were eased to allow large investment funds (such as pensions) to support venture capital. Successes such as Apple encouraged greater venture capital investment, and led to a growth in scale. In this period many venture capital firms moved away from the traditional hub of banking/finance, to the Sand Hill Road area of Silicon Valley. Sand Hill Road is close to the university, the area from which most ventures were emerging.
- 1973 marked the first tangible peak in venture capital investment: The first of several “bubbles” - short term booms in venture capital activity (measured both as number and value of investments). The 1980s saw a bubble around personal computing (121 Initial Public Offerings (IPOs) in 1983, compared to 22 the year before), finally crashing with the stock market in 1987.
- The best known boom was for “dot coms” around 2000, however bubbles continue to emerge, notably “Web 2.0″ (user-generated content websites) currently.
Although venture capital activity continually cycles through boom and bust, the overall trend over time is increasing real terms investment through venture capital.
Venture Capitalist Practices
Venture capital firms are typically small - about 20 people, primarily consisting of partners (who make deals and control the money), associates (who make deals), analysts and support staff. Firms may also have an “entrepreneur in residence” (a budding entrepreneur within the firm - termed “micro co-location”), and venture partners (sector specialists).
Firms run several funds concurrently. Funds typically run for a 10 year period. They raise money from investors (such as pension funds), and invest the equity in many different entrepreneurs’ ventures. Most ventures will fail, but a few will succeed. The successes should offset the failures within the fund. Successful ventures are sold - either as a merger/acquisition or (rarely) as an IPO. The performance of funds is commonly referred to by year “vintage”, indicating the value of returns from funds started in that year.
Venture capitalists typically take 2% of the fund as a setup fee, and 20% of the value of the final sale - colloquially a “2 and 20″ structure. Within the firm, partners take most of the 20% as a bonus to their salary.
Finding deals tends to be quite labour intensive: “doing lunch”, maintaining networks of local contacts, hosting events. Evaluating deals involves a combination of pattern recognition, due diligence, hiring in expertise, or even just following the crowd. Historically firms would invest in any sector of the economy, however there is now growing specialism, making venture capitalists “faster and smarter”. Typically each associate or partner will complete just 2 deals per year.
Venture capital firms can be characterised as passive or active in their involvement with the ventures they have backed. Active investments might involve a partner or associate as board members. Passive investments might simply stage the financing (not provide all the money up front).
Perceived Value over Time
A particularly interesting aspect of Bart’s research was the graph below (a simplified version, redrawn from my notes). It shows how “perceived values” (y-axis) change over time (x-axis).
Each line indicates the threshold which must be reached for a deal to be considered valuable by each stakeholder.
Line D (green) shows how a new associate venture capitalist (the “deal champion”) perceives value: At first they are still learning, so the line rises in the first few years.
Line P (dotted red) shows how the value of the deal champion’s work is perceived by partners: At first they are not trusted, so it will be almost impossible for the deal champion to convince her partners to commit to a deal.
Line H (dashed blue) shows the first deal the deal champion is able to convince the partners to invest in - the first to exceed line B. The “home run”, this venture becomes the focus of the deal champion. It is highly successful, and eventually its value exceeds the public market perceived value (pink line M): The venture is sold as an IPO at point 1.
Now the deal champion appears to be able to “do no wrong” - she just earnt back the entire value of the fund in one deal! The partners’ perceived value drops below that of the deal champion (at point 2) - the partners are prepared to back ventures with far lower perceived value in the belief that the deal champion knows more than they probably do. Simultaneously, the pre-dot com bubble encourages the deal champion to invest with far less care than before (line D has a far lower perceived value threshold).
Unfortunately, endlessly repeating success in such a high-risk environment is difficult. The deal champion makes many rash investments, none of which repeat the success of their first “home run”. By 2000 both deal champion, partners, and public markets have lost much of their confidence, and lines D, P and M rise again.
John Clare on Electronics Retail Margins, Scale and E-Commerce
The recently retired chief executive of DSG International, John Clare, spoke to a small group in Edinburgh on 5 October 2007. DSG is a leading retailer of electrical goods, primarily in the United Kingdom through stores such as Dixons, Currys and PC World. This article summarises the low-margin nature of the business, the drivers for globalisation and growth in scale, and makes some fascinating observations on the role of physical premises for developing a successful e-commerce (internet retail) model.
Price and Margins
Electronics retailing is characterised by infrequent purchases, with competition primarily on price: Consumers tend to decide to buy a specific product, and have little loyalty to specific retailers. Factors such as availability (”can I take it home from the store now?”) and after-sales support (”what happens when it breaks?”) are still important, but often secondary considerations to price.
Competition on price means low margins: 3-4% margin is typical on goods sold in stores (15-20% gross margin). On some goods margins are lower. A computer might retail at a price that offers a gross margin as low as 6% - not enough to cover the full cost of the sale. Creative sales techniques are required: For example, offer a free printer with the computer, but don’t include the connecting cable, the ink or the paper. Those additional items attract surprisingly generous margins - enough to offset the loses from the original transaction.
The United States market is even more price-centric: Consumers might drive huge distances to save a few cents on a purchase - without apparently considering that the cost and time of the driving may exceed the saving on purchase price. (DSG attempted to enter the US market in the 1980s, but failed. In part due to enthusiasm of Wall Street investors to encourage a competitor to grow a monopoly by continually losing money selling goods below profitable margins: In the long term, the strategy fails, because once a monopoly has been created, raising prices to profitable levels simply causes new competitors to enter the market again.)
Scale
Until 10-15 years ago, the advantages of scale in electrical retail were modest: Being part of a branded network of stores does not alter the property costs of owning local stores.
Two factors have made scale increasingly important in electronics retailing, and driven the current trend towards the globalisation of electronics retailing:
- Limited scope for growth in domestic markets: Additional growth beyond a threshold (for example, DSG’s 20% UK market share) in a domestic market becomes increasingly harder and harder to attain - it is simply easier to focus on “foreign” markets.
- “Systems” (supply chain, ordering) have become critical to reducing costs and so creating a competitive advantage. Remember, this is a sector where tiny cost differences can determine business success or failure. These systems are increasingly expensive. Walmart was cited as an example: Their systems are valued at over $1 billion. Eventually Walmart had to expand beyond the US to justify such high levels of investment in its systems.
Large established retailers in mature markets (such as France and Germany) were difficult to compete against. Instead DSG (and other large established retailers) have been focusing on “immature” markets - those still dominated by many small retailers, such as southern and eastern Europe, and China. India is also an attractive market, but lacks developed infrastructure and willingness of government to allow foreign investment in the sector.
E-Commerce and Internet Retail
Internet retailing has grown from around 1% of DSG’s sales in 2002/3, to about 10% in 2007. Competition tends to be smaller or unbranded businesses, competing on price. Consumer trust (in an established brand) and commitment to support give established large retailers an advantage online.
DSG has two distinct internet-based retail operations:
- PIXmania, a “pure play” (internet-only) retailer selling to most of Europe. The decision to acquire this business may be characterised as “hedging one’s bets”: The only acknowledged internet-only success in the EU has been Amazon. It still is not clear whether the Amazon model will transfer to other sectors.
- Existing physical retail brands, given online presences.
The second type of operation was initially similar to the first, until the introduction of a facility that allowed customers placing online orders to collect the goods from their local store:
The ability to order online and collect goods from your local store tripled online conversion rates, from 1-2% to 4%.
Customers ordering online typically collect goods outside of working hours (before 09:00 and during the evening). These are evidently people that wish to shop online rather than in a store, but want their goods delivered so fast they are prepared to travel to the store to collect them.
Conversion rates may still appear low compared to those at stores (around 30%). But the proportion of customers who are simply researching products, without the intention of buying immediately, is not known.
Improved conversion rates aren’t the only advantage for the retailer. The gross [I assume] margin on internet sales is only about 6%, with a tendency for orders to be for single items (for example, one low-margin computer, with no chance to sell money-making printer ink or paper). However, when the customer arrives at the store to collect their order, they are successfully being sold half (by value) as much again in other items. That raises the overall margin on “internet with collect-from-store” sales to 13-14%.
The e-commerce model is still being developed. Cost reductions are likely as software becomes more standardised, although retailers are simultaneously moving to higher quality, more complex systems, so cost trends are mixed. Currently internet retail operations are about 6% cheaper than physical retail operations.
That means that the “internet with collect-from-store” model has very similar overall margins to the store-only model - and both offer significantly higher margins than the internet-only model.
It is easy to overlook the constraints of slow physical delivery networks when discussing selling goods over the internet. DSG’s “internet with collect-from-store” model gives some rather compelling evidence for just how important rapid delivery is.
