[MUSIC] In this segment we're going to look briefly at a, a methodology, a very systematic methodology for experimenting with new ways of working. In some ways this is formalizing that, the sort of the bottom up approach that we talked about in the previous segment. But with a little bit more precision about it, exactly what it involves. [INAUDIBLE] It's a methodology I've worked with many companies on over the last few years. The metaphor is, is, is experimentation. And I explicitly and deliberately use the word experiment rather than the word pilot. When companies talk about pilots, they almost always mean that they think they kind of worked through all the details. They're moving ahead, but they want to have the, the option of, of, of, of rethinking it or getting out of it doesn't work. An experiment is very different because an experiment is something which may or may not succeed and it's, it's deliberate up front to say this may have a 50/50 chance of working. And I'm just going to give you two very specific examples of management experiments that I've personally overseen, both work done at Roche, the Swiss pharmaceutical, company. In teams of people working under, shall we say, the, kind of, the protection of an executive education program. And that's relevant, because sometimes, when we do things risky, we need to have a little bit of protection. And, of course, an executive education program, run through London Business School for Roche, provided them with that protection. The first one is around this notion of collective wisdom. The second one is going to be around this notion of, of of emergence. So let me just talk briefly about the two experiments. The first one was done by a group of people working in the R&D Department at Roche. And they came up with the following hypothesis. Their hypothesis was that we can tap into the wisdom of the crowd, we can get people across the organization, helping us to solve difficult scientific problems, problems that people have been struggling with. But in order to make that an interesting hypothesis, they didn't just say, that will be helpful, they said that we'll actually get more value by tapping into this internal network, than if we actually go to some sort of external network, beyond the boundaries of Roche. On the basis that those employees should be hypothetically more keen to help their colleagues and they would understand the context of Roche's specific problems better than others. So they designed this experiment whereby they identified the set of scientific problems and they asked their internal network to send out emails to all people working in R&D. Follow it up with some, some, some, some reminders and then they also posted that very same question same questions on Innocentive which is this external technology platform that we've spoken about earlier in the course where people post problems and the external network. The scientific community have the opportunity to solve those problems. Now, let's be very clear. In a sense of get a feel for this, I mean, they have to pay money to an incentive for the right to post this question and to the extent that a scientist comes up with an answer on Innocentive, they will also receive some sort of fee in return for that work. Nonetheless, by setting it up very expressively with the same problems in these two communities it was a proper experiment. What was the outcome? Well the experiment worked out, but not in the way that they perhaps originally expected. It turned out that posting the question on Innocentive gave them significantly more birth in terms of quality and quantity, responses, than by posting it internally. And in fact, I think that Roche is no different than most other large companies in that respect. It's very easy for people, employees in other parts of the company, to basically just do their own thing and ignore requests from other parts of the company. The point though is that by designing it as an experiment they learned something really useful. They learned something very valuable about how to ask specific questions and to get replies to that. And I'm going to come back to that actually in the next segment. The second experiment I want to brief acknowledge again in Roche was very, very different. It was a group of people who said look we're spending all this money on expense claims processing. You know people do a flight, people stay in a hotel, and first of all we've got to get permission to fly and you've got to make sure that you, you know, flying the appropriate class or whatever it is. And then you've got to get the expense claim signed off by your boss or your boss's boss or whatever it is. And Roche is a company that spent hundreds of millions of dollars a year on these sort of travel and hotel expenses. So, they said to themselves, this is a crazy system. Let us actually trust in people's desire to do the right thing. Let's, in the language of this course, let's move from a bureaucratic process where the expense claims are checked off by supervisors to an emergent process whereby we use essentially transparency, visibility as the mechanism for ensuring people spend their money wisely. And so they simply set up a, a, a portal on the website whereby people would post what expense money they spent. When I went on a flight, I put the money there, and the, the, the evidence for spending the money there and people simply looked at it to verify that I was spending money wisely. Again, they set this thing up as a proper experiment. They had two offices who used the traditional expense claim system, and then they had two offices where they tried this new expense claim system for the three-month period where people spent what they deemed necessary and they posted their expenditure online for their colleagues to ser, to see. What was the outcome of this experiment? Well it turned out that this transparency based approach was, was superior, superior in every respect, not only were employees more engaged and happy with this model, but in fact they were actually spending surprisingly less than the traditional model. And what the team doing this experiment felt was going on, was by creating this portal for people to post expenses. People first of all spent wisely but secondly they could also see what each other were spending on airfaires or whatever it was and that should get better deals as a result. Now, ultimately there are some challenges in scaling something like this up. Because obviously expense claims you know it's all about trapping the, the one or two people who are breaking the rules rather than the masses who are likely to be, shall we say, law abiding citizens. So there's some challenges in how exactly you scan it. But the point is, this was designed as an experiment in a way that allowed them to change or manipulate one thing, which is how we monitor expense claims and that gave them some massive learning that was usable for the rest of the organization. So those two examples are examples, I mean I've, I've, I've overseen 50 or 60 of these types of experiments, not just in Roche, but in three or four other companies as well. All done of under the guise of an executive education program. All designed to ask people to try to change things in terms of how they work, how they incentivize people, how they motivate people, how they manage their processes. The slide, final slide here, is really just a seven step summary of the principles of experimentation. As you'll see, this has some resemblance to the list I shared in the previous segment, which is the, kind of the key themes of bottom-up management innovation, using my examples from Ross Smith and from Jordan Cohen. But the point is that this seven step guide is really about people who want to develop experiments in a systematic way. And as I say, the value of this is not just that we try something and make it things a little bit better within our own part of our organization, but that we're also helping the whole organization to think a little bit more creatively and positively about the way that they do their work.
