Value propositions, hacking evolution and the Steve Jobs of Chickens

This is John’s second time on the Disrupt Podcast, and today he shares his insights into value propositions. One of the things he mentioned was the need for us to hack our evolution – especially when it comes to business, and particularly when we are working to define our business’ value propositions. This means working to understand our own cognitive biases and then hacking our ideas using customer research, insight and analysis.

Transcript:

Gavin: [00:00:00] Thanks John Dobbin for joining me on the Disrupt podcast. Can you give us a little bit of an insight into your work and your life?

John: [00:00:09] Well last time we did that we never got to the topic so very briefly I do digital transformation consulting. I’ve got my fingers in a few little start ups and I also do some mentoring at UTS and the school of entrepreneurship.

Gavin: [00:00:23] Brilliant. Okay, so one of the things we wanted to talk about is value propositions and I know that a lot of my clients and a lot of people that I have worked with over the years, really struggle with value props. And you have a particular I think insight into how you create these and how you make them stick – maybe you can share some of your …

John: [00:00:44] So let’s let’s look at this this is how long have we gone on this podcast by the way?

Gavin: [00:00:49] We aim for about 15 to 20 minutes.

John: [00:00:51] 15 to 20 minutes – we might we might go to 19 minutes and 59 seconds on this topic.

[00:00:58] Fundamentally the most important thing that any business has to do is to work out what value is from the outlook of their customer. If they don’t understand how the customer sees value, the customer is not going to buy anything. So it is the single most critical step in any entrepreneurial or business process – whether it’s a startup or an existing business. If you don’t understand what the customer’s perception of value is, you don’t understand your own business.[00:01:37] So, how good are we at this? What’s our scorecard? So there’s 100 million businesses created every year. 90 million of those fail and 36 or 38 – about half of the reason that they fail or 42% of the reason they fail is that there is no market need. Which means that people have gone out and started a business -and you and I both know how much time and effort and heartache that takes – it takes your time and your passion. They start a business and they get an investor they invest for business and they create this product – this harebrained idea where they are convinced that it’s going to be great and no one wants to buy it. So that translates to about one failure every second just because people are investing in an idea that’s got no legs whatsoever.[00:02:43] So why? How can that be? What is it that drives entrepreneurs and business people to go out and spend all this energy and invest in these ideas – that no one wants?[00:03:02] You know what is this?

Gavin: [00:03:03] What is this. What is this craziness?

John: [00:03:05] Is it hubris? Is it a calculated gamble? So if we look at this then we look at this from a very high perspective then we can find why this happens and whose fault it is. And it’s completely the fault of our ancestors – you know 100 million years ago on the on the plains of Africa because they needed to evolve to create very quick decisions.

They needed to in order to be able to survive, they needed to be able to very quickly scan the landscape and to work out where was a good place to forage. Ahh there are some green trees over there and that’s quite a good place – let’s go over there and let’s go foraging for food. But this too many animals there’s too much grubbed up then maybe maybe that’s not a good place – maybe to go somewhere else. And so our ancestors learned to determine what little signals they were in the environment where they’d be places to find food.

Similarly they were able to scan information from the environment to determine threats. So if they saw some grass rustling then that could be a beast coming to eat them – if they heard a loud flapping noise, that could be a vulture coming to take their food. So and also in terms of finding a mate, trying to read a signal to say you know is she interested me or not?

So these little cognitive processes developed and they were very rapidly executed heuristics. Now as time and evolutionary pressure evolved over the years these became hardwired.

And if you’ve ever looked at transects of a brain, it really is hard wiring. So we have to shunt information from one side of the brain to the other very quickly. So if we see a tubular looking shape in the grass we go – ahh snake! That we know what it is – we look at our memory banks and it tells our body to run away not to do anything.

So this simple heuristics are designed to make quick decisions. The problem is that we tend to overuse those when it comes to running a business because they don’t serve us very well in the complex jungle of the world. So these things are what we call cognitive biases.

So these cognitive biases are evolved to help us make rapid decisions and they’re still very good at making it helping us make rapid decisions. But in a complex environment we need to use a different type of thinking. We need to be very calculated. We need to be able to literally hack our evolution because the cognitive bias is very very very strong. It’s automatic it’s built into us.

Gavin: [00:06:08] We don’t realise we’re doing it.

John: [00:06:09] And you can’t realise you’re doing it. And so the question is how do you overcome it? And the favourite example I have is a guy called Frank Perdue and just the same way our iPhones and our phones today were irrefutably influenced by Steve Jobs. Frank Perdue irrefutably changed the course of the chickens. So if it wasn’t for Frank Perdue, we would be eating a very different type of chicken than we would today. So he was the Steve Jobs of chickens.

Gavin: [00:06:40] The Steve Jobs of chickens.

John: [00:06:43] So this guy. So he left school early to run the family chicken farm and they grew little chicks and they sold the chicks to farmers and they also sold chickenfeed and they sold the chickenfeed to farmers. And in the mid 60s he was running the family business and there was a competitor or competitive change going on in the industry. And this was the processors and what the processors were doing is that – so prior to the processors, the farmers would sell their chickens to butchers and that’s where you get your meat. You’d go down to the butcher shop and get your lamb or your chicken from the butcher shop.

The processors were coming along and what they were doing is they were slaughtering the chickens and they were freezing them and they were selling them to the grocery stores. And these companies were getting very big and like any large business, they were driving competitors’ price down. And so Frank found himself running at a loss and he needed to now – he wanted to cut out the middle man and he wanted to sell his chicks, grow the chickens and become a processor himself. Now he was up against huge market forces and so he wanted to compete on quality.

So what he needed to do is he needed to work out what was value to the customer’s perspective? Now this is pretty remarkable because this guy has grown up in his entire life growing chickens and eating chickens. If anyone knew about chickens, Frank knew about chickens but he did what most entrepreneurs do not.

What he did is he didn’t assume what his value judgment of a chicken was, was the same as the market’s. So he went out and he spoke to butchers. He didn’t speak to a few butchers – he spoke to almost every butcher in New York. He had a list of questions and he went from butcher to butcher to butcher and he’s asking all sorts of things. What do people like about the chickens? And he built up two really thick notebooks and this guy was a tireless worker – he worked 16 hours a day – so he researched this thing to the nth degree until really there was no more. The same questions were coming back the same answers were coming back again and again. And he went to the butchers because the butchers understood the quality. So how many value criteria do you think he came up with for a chicken? How many how many quality aspects – if you’re going to go buy chicken for the barbecue on Sunday, what’s your criteria – how many things would you go for?

Gavin: [00:09:31] I’m just thinking – what could you get onto the back of a label? Right so I’m thinking between 5 and 10.

John: [00:09:36] Yep. So, a bit more. So Perdue came up with 25 criteria. And then using that criteria he started innovating. So he didn’t innovate on what he thought he innovated on what his market research told him.

So, people loved the golden colour of a chicken when they cooked it so he got his team to keep experimenting with chicken feeds until they got this particular blend right full of marigold seeds. And if the chickens ate that when they got cooked, the became a golden colour.

People didn’t like the little hairs on the chicken – like in those days, they get little hairs and before they cook the chicken they have to pluck the hairs. So Frank got his team to develop to innovate create the special blow torch we’ve seen the hairs of the chicken.

People liked the fleshy breast meat – so he kept crossbreeding chickens until he came up with this chicken with this very large breast meat.

People didn’t like bruised chickens – so he came up with special handling protocols to make sure that the chickens weren’t damaged.

So this guy innovated around what the customers valued so he hacked his own cognitive bias. He hacked his assumptions. He did the research. Then once he found out what people really wanted, he started innovating around those points.

How well did he do? Well he could sell his chickens for 30% more than the market. He sold them on mass – billion dollar business and for Perdue Chickens is still a major player today.

And that is what you need to do. And so you know you and I we see, we got a lot of these pitches and people come up with these great ideas that they think is a great idea and their mum thinks it’s a great idea and their friend thinks it’s a great idea but the market doesn’t think it’s a great idea.

So I actually think the most important thing to do is – if you’ve got an idea is to hack – is it to really start to question it. And you keep on questioning and questioning and questioning until you feel that you’re getting the same answers again and again and again. And then you have an idea of what the market values in that point of time. Doesn’t mean that it’s going to be the same – if he did the research and the value proposition of a chicken now, it would be very different. But in that point in time. And that’s the discipline.

So if an entrepreneur or a strategist wants to understand a value proposition, they can not do it from the perspective of their own mind. They must do it from the perspective of the minds of the customers that are going to be selling too.

Gavin: [00:12:23] That’s right. So we call that validation right. And it’s something that we use quite extensively in the work we do but is that something that the clients understand? So we we’re talking about this that this has been around for 50, 60, 70 years if we’re following the chicken example. We know that this is the way that we should do things and there’s been proven value in this and yet it’s still something that people don’t recognise as the first step is there. Is there a gap there?

John: [00:12:56] Unbelievable – as the data suggest – one of the major reasons that businesses are failing is because people don’t want the product these business are offering. It is a – you could call it a pathology if you wanted to. It is an absolute problem – but until you, like any problem if you want to solve the problem you need to go to the root cause. And the root cause is cognitive bias. And you cannot – if you’re aware of your own cognitive bias, that’s a start but it doesn’t mean that you’re not going to become attached to an idea. It doesn’t mean that you’re going to – so one of the things I like to do is I ask the room – how many entrepreneurs are there – put your hand up. So there’s 100 people – okay, so who wants to fail? Who thinks that their business idea is going to fail? No one puts up their hand.

Already that’s a cognitive bias because the data say that 90% of them are going to fail. But they say – my business is not going to fail – I’m going to be successful. Well that’s that is a bias – it’s an optimism bias.

There are about 180 biases that they recognise you can look it up online. But basically it comes down to this idea that we tend to think of an idea in a very fragmented way from the perspective of our brain with a very – by definition a very limited amount of information. So if we really want to want to understand how the market works, we need to to research and we need to find out how the brains of our customers think.

First step – very poorly done – a huge opportunity for people to do it right.

Gavin: [00:14:53] So if that’s the case and if we’re seeing this a lot and we as the data show us we are finding this is the case, what are some steps that we can take to reduce our bias or to test our biases? Not to put you on the spot.

John: [00:15:12] No no no. It’s very simple. So you have you have an assumption about your business. Call it a theory or a hypothesis. So how are you going to test that hypothesis. If it’s a very lightweight product an Internet based product. Yep. Rather than going out and interviewing customers it might be easier for you to throw up some landing pages and to see how it takes it. So that’s that is a way to test your assumptions. But if it’s a big business, if it’s a big idea then the first step is you go out and you talk to people and you ask them questions. It’s a radical concept – but it’s not just talking to people because you also have to talk to people in a way where you don’t allow your cognitive bias to affect the conversation too much.

So we talk about hermeneutics in social sciences. We talk about hermeneutic research or the phenomenological research and it’s a way of actually asking questions so that you’re not imposing your ideas. So for example if I said you like do you like this vase here and you say yes or no. That’s not a very good question. A much better question would be – Gavin tell me the process that you undertook to go and buy that vase and why did you choose it? And you might talk about you were walking past a shop you might talk about all sorts of things but I’m going to be listening without an assumption about why you bought that vase. And we can go on for hours about how to do this but the important thing is to try to say – just because I believe in my idea doesn’t mean other people do. And if they disagree with you, you don’t try to argue with them saying, if I say that’s a very poor vase and you say it’s a good vase – you don’t fight about it because you have to listen to the customer.

So it’s a process of deep deep deep listening and trying to suspend your judgment, trying to suspend your ideas and writing this down and then seeing what the data does after you’ve done enough of these interviews.

Gavin: [00:17:27] Interesting. So it immediately makes me wonder – with this big push that we’re seeing at the moment on the tech side of things around artificial intelligence, is whether we’re building in to our artificial intelligences some form of cognitive bias, or not or whether that’s a danger that we’re not foreseeing at this point in time?

John: [00:17:52] So if we look at if you look at the way an AI is built. So if you look at a convolutional neural network, that is trained by yes our no decisions. Is that a vase – yes or no? So if the training is objective then the AI will be objective. If we start to say this is good or bad – that’s a good vase or a bad vase – then we are starting to impose a subjective experience upon the AI. It’s just a machine that’s going to recognise a pattern and repeat that pattern.

Gavin: [00:18:29] What goes in also comes out.

John: [00:18:32] If you’re looking at the more advanced types of AI using causal inference and Bayesian networks then then it’s much more susceptible to bias because you are trying to tell the AI this is why this particular thing is important or if you do this then this will happen. So you want to be fairly careful with those instructions to make sure that you’re not imposing some sort of bias upon that.

Gavin: [00:19:04] Interesting. I knew you’d have a good insight into that one. Brilliant. Well thanks John. It’s been an awesome exploration of value propositions and I think you’re right, we could probably talk for many more hours on this topic and delve into some of the challenges of how you actually validate and why you validate and when you validate and so on.

John: [00:19:26] You validate all the time all the time.

Gavin: [00:19:28] Always be validating.

John: [00:19:29] Always be validating.

Gavin: [00:19:31] Awesome, Thank you John.And we’ll speak again soon no doubt.

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