Earlier we talked about how clients come in many shapes and sizes. They're very diverse. And they hire consultants for many different reasons, right? Some are kind of very intellectual where they want to come up with the most logical answer to a problem. Sometimes it's just more emotional, right? They're afraid of making a decision and they want your help to get them kind of off their seat. And sometimes just here on the right hand side, they just need help. It's like we kind of know what we want to do. We just need help doing it, right? What I would say is that data and data analysis plays a part of all of this. And so I highlighted some things in blue to emphasize that, right? So connecting junkie data that's sitting in different places. Driving the data not just to information because information is better than data, but it's really not enough to act on, right? And when clients hire you, they want help and being objective, getting through all the politics, getting people on board, so that they can really make the change. We talked about in the last module that you build a lot of credibility with a client, right? You take something frankly, a little bit ugly, a little bit messy, and you build credibility and create a common set of facts to work on. Now, you may not always agree with your client, right? They believe X and from your experience, working in the industry, having seen other competitors, and you know in their situation from your professional judgment, you may disagree. That's okay, that's possible. But you're working from a common set of facts, right? You're not arguing about definitions, you're not arguing about their current market position. It's a fact, right? And that's a beautiful thing. Once again, the real treasure, what we're trying to get at are the insights that give the client enough confidence and a road map to make some changes. So like the name of this module, like okay, what's this look like? This is a graphic we've used before showing that the confidence that you and the team as well as the client has on the recommendation, it's not a straight line, right? This is not like school where you know exactly three months later what your score is going to be, right? It's not like that, right? Life is a lot lumpier, consulting is a lot lumpier. So you see a lot of up and down here in confidence because frankly, you're getting smarter as you go, right? So let's go through some of those things. So as you get more data, you can see here, you're getting smart by yourself before you start interacting with a client makes sense. But then you get some data you get some more data, you analyze it and then over time, over the project, you become more confident, right? So that towards the end, I mean frankly, you're kind of fired up, right? You're kind of willing to fight about it, right? Because you believe this stuff, right? So starting at the bottom left where you didn't have a lot of confidence because frankly, you didn't know what you didn't know, towards the end where you're just being very aggressive, right? You've done the work, you've thought about it a lot. You validated, you've taken data sources that the client didn't even know about, right? This is where the power dynamic changes a little bit where you should have really strong opinions about the analysis that you've done. So in the early days, lots of activities, some people might say scrambling. You're sending a data request to somebody. You've send it to the wrong person. It comes back. You've send it again. What they send back is only half of what you need. You take a look at it. It's a little bit junky and they're a bunch of missing fields and you have to validate that. So number one, even though it looks very simple, even though I just said, hey, the analysis looks good. Trust me, it is not good the first time you get it, right? So there's a little bit of, you do something and you just keep refining it, so one can take a while. You get it clarified, you refine your hypotheses. You get back on track, because towards the second half of the project, what happens, you start bringing in different data and they call that cross-walking. Cross-walk is just a simple way of saying, getting this data and this data to connect, right? You kind of map it together. So your combined data set is bigger. That's all it is, right? And so, you can see that we're definitely climbing the confidence hill. So towards the end of the project itself, you're feeling pretty good. You're feeling pretty good. And you have not just one recommendation but a set potentially of recommendations that work together. So here's a client. I did six years in healthcare consulting and so here's an example of a client that I had. The client before, when we first started the project. They said stuff like, look, we need more operating rooms. We don't have enough capacity. We're always busy. Heck, we're turning away patients, we don't want that, right? We need more rooms. That's what they kept saying. Well, you can already guess what the punch line is, right? I have a blank here on the right hand side. Take a guess on what the data said. Well, the data said actually, you don't need more operating rooms. Are there are many problems where the operating rooms were either empty, or needed to be cleaned, or there wasn't a patient there, or the surgeon was late, right? So without having data, there's just no way to push back on the client. There's no way to help the client understand that it's a lot cheaper to improve your scheduling process, right? It's a lot cheaper to make sure the surgeons are on time. It's a lot cheaper to make sure that they have transportation right between the testing area and the ORs. In the end, data keeps you safe, right? Data helps you to make good decisions. Data helps you to bust myths, M-Y-T-H, that the client might have. Some key takeaways. One is just stay curious. When you hear things at the client side, they're not always true and some of it is just a legend, right? So here I say, trust but verify, right? Don't call anybody a liar. Don't call people out. That's not smart. But also let the data do the talking, okay? So stay curious and continually refine your questions. Just like I showed that the confidence you have over the project increases over time but not in a straight line. What I'd say is that the green graduation caps, the new hires, the newbies, a lot of time, you are the least experienced person on the project, right? You're 24 years old, everybody else is 37, and they've been working in this industry for many years. So you're kind of at a disadvantage. Right. However, what I would say is there's a strong likelihood that you are the most experienced person with this data. So even though you might be new to the industry, no one and I'm serious, the client or even the partner on your side of the table, no one at this table understands the nuances of this data and what the analyses really mean more than you.