Value Driven Data Science

[00:00:00] Dr Genevieve Hayes: Hello, and welcome back to Value-Driven Data Science, where data professionals become strategic experts. I'm Dr. Genevieve Hayes, and I'm here again with Blair Enns, author of The Win Without Pitching Manifesto and The Four Conversations: A New Model for Selling Expertise. Last week, Blair and I discussed Blair's expert AI manifesto and what it means for data experts.
[00:00:27] Today, in this Value Boost episode, we're exploring Blair's Four Conversations framework and how data professionals can use it to sell their expertise, either as independent consultants or as employees within an organization. Welcome back, Blair.
[00:00:46] Blair Enns: Thank you, Genevieve.
[00:00:47] Dr Genevieve Hayes: The number one piece of advice I give to data professionals is to have more conversations.
[00:00:53] Conversations lead to good things, and I owe many of the best opportunities I've encountered in life to proactively seeking them out wherever I can. This podcast is a weekly example of the power of conversation. However, if there's one thing all these conversations have taught me, it's that good conversation is a skill, and that conversations go a lot smoother if you go in with a plan.
[00:01:19] Without a plan, you can end up walking away with nothing more than a vague promise to keep in touch. The Four Conversations framework outlines such a plan. So Blair, can you give us a quick overview of the Four Conversations framework and the problem it's designed to solve?
[00:01:36] Blair Enns: Sure thing. So it's the framework, it's a model. It's our view of the world. Your audience might know who Professor George Box is, as I'm fond of saying he's an author and statistician who's famous for this one quote, which is, "All models are wrong.
[00:01:51] Some are useful."
[00:01:52] I think that's his biggest claim to fame. So in my book, "The Four Conversations," I say this is a model to think about the how to sell expertise. And I lead with Professor Box's quote because what I don't want to hear is , it doesn't really take four conversations."
[00:02:08] I know the sale isn't always a series of four linear and discrete conversations, but it can be helpful to think of it that way. So in this model, we see the sale as a series of four linear and discrete conversations. Each is self-contained, each follows the other seamlessly.
[00:02:25] Each conversation has its own objective. So at any point in the sale, you simply stop and ask yourself, "Wait a minute. Which conversation is this?" It's the qualifying conversation. Okay, what's my objective in the qualifying conversation?
[00:02:39] It's to vet the lead to see if an opportunity exists and determine the next steps. Okay, now that I know where I'm going in this conversation, how do I get there? And so it's every conversation has a framework or a set of frameworks that you use to help navigate to the conversation's objective. So I use the qualifying conversation framework. Now, in addition to framework, the model also has principles, ideas that you embody as you're using a conversation's framework to navigate to its objective, and that's it in a nutshell.
[00:03:12] Frameworks as a tool to navigate to a destination reside right in the middle between scripts on one end, highly scripted, and then no plan at all at the other end.
[00:03:26] Does that make sense?
[00:03:27] Dr Genevieve Hayes: Yeah.
[00:03:28] The four conversations framework is built around moving from being seen as a vendor to being seen as an expert.
[00:03:36] For data professionals, that vendor trap is very real. Data professionals are often treated as a pair of hands that's just there to execute technical tasks rather than as the strategic advisor they have the potential to be. How can this framework help a data professional to escape that dynamic?
[00:03:56] Blair Enns: So there's two parts to dealing with that, moving from the vendor to the expert position in the relationship. And I make the generalization in the model that there are only two roles that you might occupy in your relationships with your clients and your prospective clients.
[00:04:14] If you're not seen as the expert, then you are just another vendor. So it's the expert or a vendor with very little power in the buy-sell relationship.
[00:04:23] So the probative conversation is the first conversation. It's the most different from the other three because it's a conversation, in air quotes, that happens without you present.
[00:04:33] The idea here, and only here, of a conversation is a construct. So there's a conversation being had without you present through your agents of your reputation. And so by building reputation in the market you serve, that's you moving from just another vendor to the expert.
[00:04:52] And then ideally, you drive an inbound inquiry, or maybe it's an outbound inquiry, and that person is familiar with you and your reputation. And now right from the first person-to-person conversation, the second one, the qualifying conversation, you are occupying the expert's high ground.
[00:05:09] Now it's your job to not give up that high ground by suddenly behaving like a needy vendor. So there's this function of building reputation in advance and then not destroying that reputation through how you sell, and typically that's done by importing sales techniques from other domains that are okay with the collateral damage of reputation, where there's no real reputation being harmed.
[00:05:39] Selling expertise is different than other forms of selling because when the prospective client is dealing with the expert they will work with, they're paying attention to everything that you say and how you comport yourself, your attitude, how you show up in that engagement, and they're trying on what it would be like to work with you, and they're looking for reasons not to hire you.
[00:06:02] So you have to sell the way you deliver, The model is built for people who are already professionals, already expert advisors or practitioners, and take that way that you show up in your engagements with your clients and then sell that way.
[00:06:18] Use this framework to let that person step forward and navigate through the sale the same way you would navigate through an engagement
[00:06:28] Dr Genevieve Hayes: And one comment I'd make here is even though this book is written in the context of experts who are running a consultancy and literally trying to make a sale. I would argue that everything you write in this book can also apply to data scientists who are working as employees within organizations.
[00:06:50] Because even though they're not making a cash transaction, they are still trying to sell their expertise in getting their proposals approved by senior stakeholders, for example,
[00:07:05] Blair Enns: yeah I agree with you. That wasn't the audience I was writing to, but I'm fond of saying the target isn't the market. The target is that at which you aim, and the market is the larger area you're happy to hit. So I do understand that a lot of the principles and frameworks in that book really are relevant to how you operate inside a larger organization. The principles are really the principles of how any expert should behave in any engagement, therefore how they should behave in the sale itself.
[00:07:36] Dr Genevieve Hayes: So for data professionals who want to start applying the Four Conversations Framework tomorrow, is there something you can leave them with ?
[00:07:45] Blair Enns: So I have four children. They're all my favorite. And I have four conversations. There are four conversations in this model. They're all my favorite. But I think the game changer is the value conversation. And I do a lot of talks in which I open with the question, "If a tree falls in the forest and there's nobody there to hear it, does it make a sound?"
[00:08:06] And I get everybody in the audience to vote, and almost everybody says, "Yes, it makes a sound." So they're wrong, because I point out a tree falling in a forest creates a sudden change in air pressure that ripples throughout the forest and shakes the leaves But if there's no eardrum present to translate that sudden change of air pressure into noise, then there is no noise because noise or sound is a property of the observer.
[00:08:30] It exists in the mind of the observer. And then I make the point that it's the same with value. Value itself is a property of the observer. So in the value conversation, you're endeavoring to uncover the value that resides in the client. Now, a lot of my audience is marketers who are in sales roles.
[00:08:48] So In marketing, you're basically broadcasting messages of value to an average of a segment. So you're saying, "What does the average person value?" And you create a value proposition that's designed to communicate one to many. Now, there's a great book called The End of Average by Todd Rose, who says it doesn't really matter how big the audience is, and it doesn't really matter how many dimensions you're measuring in that audience. When you look at the average that you come up with for that audience, and then you try to determine how many in the audience are exactly like the average, the answer is effectively zero.
[00:09:28] What we take from that is When you're making claims of value to an audience, as marketers do, your value proposition is approximately right for many, and it's exactly right for effectively none. When a marketer shows up in a sale, and not just marketers, a lot of people do this, they think it's their job to make claims of value.
[00:09:53] It's not. It's your job in that moment to recognize that there is no value inherent in your services. The value is in the client. And if it's an internal conversation, then it's the internal stakeholder who you have to convince about this project, or you have to uncover what is it that they want.
[00:10:11] How can I help them? What's the value they're seeking to create? So the value conversation is a simple four-step framework designed to help you get out of this mode or mindset of that I have to communicate my value, 'cause you're gonna communicate it wrong. You might be approximately right; you won't be exactly right.
[00:10:29] So it gets you out of that mindset, and It gets you focused on what's the value this person wants, and then it gets the client focused on this. And at the end of the value conversation, you have this alignment about this beautiful vision that the client wants to come true, and the value of that vision coming true, and the metrics that you'll measure to determine that vision came true.
[00:10:50] Dr Genevieve Hayes: As a data professional, everything that you just said there can apply if you just replace the word marketer with data scientist. We data scientists try and communicate the value of the work we do. But what you're saying is if you want your stakeholders to value your work, you need to uncover what it is that they value and be able to communicate how your work can create that value for them.
[00:11:20] Is that right?
[00:11:21] Blair Enns: Yes.
[00:11:22] Dr Genevieve Hayes: So if we're going to leave our audience with one piece of advice regarding that, what would that be?
[00:11:28] Blair Enns: Just embrace this idea that the value resides in the client. Everybody values everything differently. Even economic value is a little bit of a head fake. It's not even what that person or the organization might do with that money that might be created. It's how this human being feels about what that money might do for others.
[00:11:50] And sometimes it's not even about the money, even when it's ostensibly about the money. At the end of the day, value is nothing more than a feeling. It is a sense of regard.
[00:12:00] Dr Genevieve Hayes: So from a data professional point of view, you'd have the value of being the person who understands what's going on because they've got the numbers to be able to explain it
[00:12:13] Blair Enns: In a value conversation, let's say you uncover the value that might be created by the work that you might do. Then ask the person what about you personally? What would this mean for you in your day-to-day and maybe even your career if this vision of success came true and we hit these numbers?"
[00:12:30] Somebody might say two years from now I'm not even here. I'd get promoted out of here if this goes well." There are the corporate objectives that are gonna come up, but it's a human being
[00:12:40] that you're dealing with, and their motivations are entirely personal to them, Even when they're executing on corporate objectives.
[00:12:48] Dr Genevieve Hayes: That's it for today's conversation with Blair. If you haven't already, listen to our previous episode where we discussed Blair's expert AI manifesto. Thanks for joining me again, Blair.
[00:13:00] Blair Enns: Thanks, Genevieve. I've enjoyed it.
[00:13:02] Dr Genevieve Hayes: And for those in the audience, thanks for listening. I'm Dr. Genevieve Hayes, and this has been Value-Driven Data Science.