Earlier this week I did a talk on innovation for a local firm that was the opening session of their strategy-making work for the year. During the questions, one person asked for suggestions about a specific initiative that they had been trying to get off the ground for a couple of years, but which just kept stalling. Before I could even answer, someone else jumped in and suggested that maybe the problem was that they simply hadn’t figured out yet how to test out the idea quickly and cheaply.

I’d like to say that he came up with such a great answer as a result of my inspirational talk, but I think that the truth of the matter is more mundane – he’s a smart guy. They talked about some of the ways that they might try an experiment to get the initiative off the ground, and the discussion gave me a clue about how to integrate a couple of ideas that we’ve been talking about here recently.

I’ve talked frequently about the importance of experimenting in innovation, and John has been discussing the use of real options in costing innovation initiatives. The key question is: what do these ideas mean in practical terms? Saul Kaplan makes the case compellingly in his post Think Big, Start Small, Scale Fast – here’s a quote, but go read the whole post:

Systems transformation is all about experimentation. It is about combining and recombining capabilities from across silos until something clicks and value is delivered in a new way. It is never just one thing. It starts with a big idea that gets the juices flowing and attracts others with similar passion to the purposeful network. The big idea has to be translated from the white board on to a real world test bed to demonstrate that the idea is feasible. Starting small and demonstrating progress is key to building credibility and expanding a network of interested stakeholders. An ongoing portfolio of small-scale experiments to fail fast on those without merit and to prioritize those with the potential to scale is critical. Those experiments that demonstrate the feasibility of a new model or approach become candidates for expansion.

There’s a great case study of how this can work in Seizing the White Space: Business Model Innovation for Growth and Renewal by Mark Johnson. One of the cases that he describes in detail is that of Hindstan Unilever (HUL), and their introduction of the Shakti Programme. You can read more about this initiative in this article from Fast Company – I will just focus on a couple of the key points.

The goal of the scheme was to reinvent the firm’s distribution model. Previously, they had sold all of their personal care products through stores in India. Unfortunately, the majority of the population of India still lives in villages, most of which don’t have stores – which meant that HUL was unable to get their products to nearly 60% of the population.

The Shakti Programme set up a completely new distribution channel – HUL helped local women set up their own entrepreneurial ventures within the villages. The women, called Shakti Ammas, received training from HUL, and then sold soap, shampoo and other small goods door-to-door. This was a radical business model innovation.

How did they do it? They started with a group of 17 women – this was the experiment. The point of the experiment was to figure out if they could help these women set up their own successful businesses by helping them build their skills, to figure out if there was sufficient demand for these products in the poorer regions of the country, and to sort out how to best build the distribution network. In the second year, they expanded the program to sixty women. During this time, the focused on learning the answers to the first two questions. Then they expanded to 2800 women covering 12,000 villages – this was still an experiment, and it was designed to address the third question.

The experiment was a success. They learned that in this model, the real customers were the Shakti women, and so the supply chain was built around meeting their needs effectively. Once they had proven that there was a market in these villages, that they could successfully train local women to effectively reach it, and that they could build a supply chain that could scale, only then did HUL invest heavily and roll it out through the entire country. There are now 45,000 Shakti Ammas in India, covering over 100,000 villages. The program is profitable (low margin but high volume) and it has become a substantial source of revenue for HUL. Furthermore, they are getting ready to start experiments to try out similar programs in other developing countries.

This case illustrates several key points. The first is that it is a great example of how to experiment. The small launch, with just seventeen women, was relatively inexpensive, and it was designed to answer specific questions. Even if it had failed, HUL would have learned valuable lessons about how to work in the villages. And if it had failed, no one would have ever heard about it, because it was a really small experiment. These are the kinds of experiments we should be trying – small ones, aimed at answering specific questions.

This also illustrates how the real options approach works. Instead of evaluating whether or not they should try out a program employing 45,000 women covering a huge geographical range – which would have looked awfully risky – HUL was able to make scaled investments. The real options approach is designed to figure out how to do exactly this – scale your investments, with clear ideas about whether or not to proceed to each new step. You can see how this worked for HUL – at each step they could have pulled out if the experiment hadn’t worked.

Here are some conclusions:

• Follow Saul’s mantra – think big, start small, scale fast.
• Set up your experiments to test specific questions.
• Make sure that you learn from experiments that don’t work.
• Use a real options valuation approach to valuing your projects.

Whenever you are trying to get a new innovation off the ground, ask yourself how you can test it out cheaply and quickly. People are much more willing to help you scale up a project that has already been demonstrated to work, than one that is just a great idea.