Let me propose that the best use of resources (time and money) in the startup process is to reduce risk.
If lowered risk translates into higher valuations when the business either attracts investors or is sold, then lowering risk for the lowest possible dollars creates very high returns.
For instance, if a business plan with a sound idea is interesting, it may be valued at or below $1MM. If, however, the basic business assumptions that would make the idea interesting are proven to be achievable, the value may well leap to $2MM. If customer interest can be obtained in a live test involving revenue, valuation may rise again. And so forth through team building, developing expense structures, etc.
The idea, therefore, is that TESTING for results is one of the fastest ways an entrepreneur can increase the valuation of her business.
It seems that entrepreneurs often test by committing relatively large amounts to rollouts of products or services based on planning and on expectations based on experience – but not often on testing. In this way they spend too much relative to the amount of risk they are reducing. When they miss their projections, the cost to recoup and try again is often prohibitively expensive.
Examples of testing lessons learned:
1. In a seasonal retail business, the temptation was to rollout to as many venues as the entrepreneur could afford, rather than “miss the summer season.” But, when the results were disappointing, it was hard to find the money to use the valuable lessons learned and adjust because the cash was mostly gone.
2. In an “elephant sale” software company ($200,000 average order) the staff and infrastructure was built to sustain sales of $400,000 per month, beginning three months from product release. Unfortunately the sales process was untested and did not work as well as was hoped. The company quickly ramped up losses faster than expected, putting pressure on a new financing round at the same time as disappointing results were being reported.
3. In an e-commerce catalog, new catalog releases follow a specific plan. Very small inventory orders are placed, and ad strategies for traffic are tested. An algorithm is applied to predict orders after the first two weeks. During the next month, additional inventory is purchased, again in small lots, and at relatively higher costs. Why? At the end of six weeks, the company can accurately predict demand for six months, place larger orders, reduce costs, and successfully launch with minimum risk. And, if it is a flop, it doesn’t cost much, leaving lots of cash for the next test.
Testing. Try it. You’ll like it.