Regulation is often used as a scapegoat for a company’s decision not to truly embrace an innovation agenda and the practices that support it.

“We can’t experiment with new products because we have our operating licenses to maintain, a reputation to protect and shareholders to serve” is what many a corporate executive will tell you.

However, in an era where listed companies have a one in three chance of being delisted in the next five years (six times the delisting rate of companies 40 years ago!), large organisations simply can’t afford not to experiment given that it is critical to the development of disruptive innovation and new business models, what organisations need most right now.

But how does one experiment when a corporate watchdog is breathing down your neck and watching your every move?

Experimentation Is About Testing Assumptions, Not Finished Products

First, we need to be clear about why and how we experiment.

If you’re a large insurance company then it’s not a matter of simply releasing a new policy via your website to the public and testing whether or not anybody bites.

As an insurer, any new insurance policy would no doubt require regulator approval before release to the public, which would add significant time and cost to the entire process. This goes against the nature of experimentation which is all about moving quickly and taking lots of small bets to determine what customers like and what they don’t like in order to support strategy and find opportunities for product market fit.

So how do you move quickly then?

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Experimentation is about validating key assumptions that underpin a business model.

For example, if you’re thinking about launching a new online peer to peer lending service targeting young adults you’ve got a few key assumptions to test which might include:

1. There is a percentage of young adults that aren’t satisfied with existing lending channels
2. These young adults are not credit risks
3. Young adults would use an online platform to borrow and lend money
4. Interest rates charged are sufficient for both borrower and lender

These are but a few key assumptions that may apply. Others might extend to different aspects of the business model such as distribution channel, payback periods, customer profiles, customer acquisition strategies, fees and so on.

Taking the above example though, do we really need to go through the motions of building, releasing and promoting a full blown peer-to-peer lending solution to simply test whether these assumptions hold true? Of course not. That would be fiscally irresponsible, a case of “me too” and putting the cart before the horse.

These assumptions can be tested using a combination of tools such as design thinking exercises, online and offline surveying, consumer credit reports and hitting the streets.

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A Case Study in Getting Out Of The Building

Medibank, a listed Australian private health insurer with a market capitalisation of AU$6.9B, hit the streets to test some key assumptions underlying its Gym Better product, a policy that targets gym goers or ‘would-be’ gym goers with casual access to a number of partner gyms across Australia. I personally find this particularly appealing as a health conscious professional who often travels around the country but is not a member of a large franchise gym. Paying $25 to $30 for a casual gym visit is hardly ideal!

Medibank didn’t simply release the product because this would have required regulatory approval, thus requiring a massive time commitment and financial outlay. Not only that, but spending all that money to release a product to market without sufficient customer validation up front is a recipe for disaster and the number one reason why most new ventures fail.

To that end, a new corporate venture is no different to a startup in the sense that they are both new temporary institutions looking for product market fit and a scalable, repeatable business model.

Instead, the insurer dispatched a number of staff in plain clothes with iPads in hand to the busy Bourke Street Mall, in the heart of Melbourne’s CBD. They were able to validate and more importantly perhaps, invalidate some of the key assumptions underlying their business model by simply speaking with gym goers and the like.

This was their way of refining their product before over-investing in a flawed one. In some cases where willing participants expressed their interest in buying the product, they were simply told that the product doesn’t actually exist and were offered some Gold Class movie tickets for their time. Everybody wins!

In addition, health insurance agencies in Australia can only change their price point once a year on April 1. Getting a better idea of price point directly from target customers before going to market is obviously important, less you want to release a product that’s priced poorly and have to stick by it for up to a year.

Gym Better has gone on to be a much talked about addition to the suite of products that Medibank offers, giving members access to over 600 gyms.

Experimentation Leads to Efficiency

So much of what companies do is based on efficiency, so much so that we’ve created ratios and metrics to measure effiency such as Return on Investment (ROI), Net Return on Assets and Internal Rate of Return (IRR). As a result, managers often focus only on the D in R&D in order to bring down the denominator and increase the chance of healthy short term returns.

This generally supports only replicable, safe, incremental innovations that serve only existing customers and don’t help companies carve out new markets or catch new S-curves which is critical at a time when, need I remind you again, one in three public companies are at risk of being delisted in the next five years alone.

However, what if experimentation actually supported efficiency? Well, it does.

Products developed using traditional methods such as ‘waterfall’ are said to fail 75% of the time.  

While waterfall might make sense when developing what is known. It simply doesn’t lend itself to experimenting with potentially disruptive innovations when there are so many unknowns to contend with. When waterfall projects fail, a big part of the reason goes back to market failure and not having a strong enough understanding of the customer, the problems they are facing and gains they are trying to create.

Experimentation helps us identify those flawed assumptions before investing in building finished products. It supports releasing products to market only once comfort has been gained around the proposed business model and its revenue generating potential.

As such, if identifying and tracking assumptions and metrics correctly, you can pull the plug on doomed projects much earlier in the piece because of a more intimate understanding of customer needs and re-allocate to more promising endeavours, thus improving efficiencies over time. Methodologies like the lean startup help to keep risk to a minimum and align with company risk profiles, a key aspect to getting buy in from senior executives as well.

(Check back next week for Part 2 of this blog, where Steve talks more about innovating in a regulated industry, including the importance of taking a portfolio approach, and dealing with infrastructure concerns)