Digital Transformation And Innovation (Part 1)

[00:17:02] That is more often done despite well meaning people, the folks that know the business the least tend to over accelerate when the time to value is going to be. Meaning they reel it in so that it’s sooner instead [00:17:20] of understanding the real impact on operations and individuals. 

[00:17:25] Alexander: Yep. People generally overestimate how quick things can change.

[00:17:33] Yeah. No, quick things will change. Yeah. So especially when it comes to [00:17:40] change things always tend to change. To be longer than expected, more difficult to be expected. And there will definitely be things coming up that you have not expected. And so with the discussion today, we’ll go through a couple of these potential problems that you will [00:18:00] face.

[00:18:00] Yeah. And that will hinder you in terms of the speed to value as well as how much value you generate. Overall, yeah, so both things kind of play a big role if you think about this like a S curve. Yeah, from low, low value [00:18:20] to high value. Yeah, we speak about, you know, how stretched this S is, how long you get from low to high, as well as how big the overall gap is.

[00:18:33] Or gain actually will be, you know, so blow both driven by these five things. Yes. [00:18:40] Okay. So let’s start with mindset.

[00:18:42] Chris: Okay. There is a lot under mindset, certainly more than the two bullets that I have, but I believe that this will start to give a flavor. One of the things in my experience of Leading cross functional [00:19:00] teams. So leading digital or I. T. Teams business teams. There can be quality teams that are involved in the terminology that the nomenclature and the understanding.

[00:19:14] And there, there are times that let’s pretend you and I didn’t have kind of the same, [00:19:20] the same background we could say actually the same word. Yeah. So, so the phrase just as an example, integrates data. To data management is going to mean something different to a statistician. For example, integrated data is multiple collection [00:19:40] sources being assimilated and integrating data to a statistician typically is going to mean a cross study, right?

[00:19:47] So you can say the same words and I’ll think that you’re, you’re going forward together and not. So I find that it’s best to get a level set on terminology, [00:20:00] and optimize and innovate and share some characteristics that are the same, but really, they’re different. So this is the Chris Colangelo definition of these words for our conversation here.

[00:20:16] Optimize takes the way things are [00:20:20] and makes it as good as it can be. And innovate says. There’s a better way to do it. We can fundamentally change and it’ll be better. So as a statistician, if we were to think in terms of like [00:20:40] conditional probability, it’s basically the same way we do it. Just do it better.

[00:20:46] So get a faster horse like Henry Ford is credited with saying, as opposed to let’s make a car right it is an example of an innovation. And so if the [00:21:00] people just want to keep the same, but make it better, that is obviously going to limit. The ability to change in a radical way. And so to protect something is different than to maximize [00:21:20] value.

[00:21:20] There’s an example that I could use in a couple of places here. Cause I think it would apply. There is a well meaning management out there that has said, Hey, we have spent years building up our library of standards for just an [00:21:40] example. And we have a library of SAS macros that is amazingly complex.

[00:21:48] So whatever you build has got to make sure that we, we use all that now that touches upon. Business continuity and [00:22:00] transition, but it also touches upon, oh, I have a limitation and how I could change because I have to link back to what, what exists. And there are other examples that just came to mind for me.

[00:22:15] So when we go to maximize, it’s basically [00:22:20] I’ve got, I’ve got a clean slate and how do I take what, what we do. And break it down into what is minimally necessary to do it and then build it back up or architect it in a way that uses the most modern technology that [00:22:40] uses our information that uses our current expertise coming out of universities and schools.

[00:22:50] Because that’s different now than it was 10 20 years ago. How do we take advantage of all that to be as modern as possible on [00:23:00] what we must have in order to run a compliant and efficient business? 

[00:23:07] Alexander: Yeah, and I’m the endless examples of that in terms of optimize versus innovate. One of my favorite examples is delivering tables.[00:23:20] 

[00:23:20] There is an endless amount of optimization going on in delivering tables faster with higher quality, with less cost, all these kinds of different things. When my question very often is, do we actually need tables? So [00:23:40] I have another episode that talks about tables are not hierarchy deliverables. Very often, we don’t need to deliver a table.

[00:23:52] And when I say that to people, some people think like, Alexander, you’re crazy. Of [00:24:00] course we need to deliver tables. This is how we generate value. And I say, no, we don’t. We could generate some kind of interactive graphic. Yeah. And it would provide more value be much cheaper, easier, and all kinds of different other things [00:24:20] for the purpose that we want to get to.

[00:24:23] And doing that is incredibly hard. Because of this mindset issue. 

[00:24:32] Chris: I absolutely agree. And so to, to, to add on to, to what you’re saying [00:24:40] there, there is a need for data to create an interactive. Visualization or, or whatever else it winds up being. And so there’s a mindset. It’s more of an old school mindset.

[00:24:58] It’s very [00:25:00] understandable because we grew up this way that. I’ve got to create a table or a figure or listing. And you, I, you can credit many software companies, but I think SAS gets the main credit for that, right? So that was the way that we stored statistical analysis [00:25:20] results. And it was also the way that we reported or conveyed them, communicated them to someone else.

[00:25:28] An example of being in a different age right now between a digital age and information age. Is if, if we look at a table figure listing [00:25:40] everyone’s familiar. It could be SAS, it could be R it doesn’t matter how it was created. There is a component of, of results. And then there is a way that the results are outlined or styled or structured.

[00:25:54] And if we break that apart so that we can database the [00:26:00] results, then there is a wealth of opportunity. To feed a visualization, whether it’s dynamic or whether it’s interactive, there’s the opportunity to later create a table figure listing. If that is needed, there’s the opportunity to flow those [00:26:20] results to something that has to do with data mining or or AI or machine learning where it could be combined with other things to gain new insights.

[00:26:30] I just rattled off three or four use cases for those results. That create great operational advantage by [00:26:40] isolating the actual statistical analysis results electronically versus how they are reported or communicated on. And so, yeah, that that can be hard for some folks to get their their mind around. That’s a great example. 

[00:26:59] Alexander: Okay. [00:27:00] Mindset is one of the key things and really look out for the mindset that is within your organization, is within the people that you want to take with you through that transformation. Kind of there’s a smaller brother of mindset [00:27:20] is emotions. What are your main thoughts about, you know, how emotions can hinder your transformation?

[00:27:30] Chris: So one of the implications of what I said before, but I’m going to say more explicitly now, is [00:27:40] that anyone can come up with the greatest future state. Can use the greatest latest sexiest technologies. But if we’re rolling something out to 500 users [00:28:00] and the 500 users go, I don’t like it. I’m not using it.

[00:28:05] You’re not going to get value from it. And so this is the first bullet is really for the organizational change component of this. And [00:28:20] I’m gonna pick again. I am. I am more diverse than a I, but I’m gonna pick on a I because I can tap into something that you said before it is. It is kind of the fear of the unknown.

[00:28:32] And so when when a I is doing something. It is almost seen by some people as [00:28:40] magic. It’s, it’s almost similar to having a black hat and pulling a rabbit out when you get some insights from, from AI. And there is a general concern that AI is going to make my expertise obsolete or, or replace me.

[00:28:58] And so there’s [00:29:00] only a half hearted acceptance at times when. There really is opportunity. And, and so it is how there is a management of this, and it, it relates to the communication part that we’re going to get to in a moment. And it really, [00:29:20] it gets to focusing on the bigger picture. So we are in the middle of the fourth industrial revolution right now, meaning we’ve had three industrial revolutions.

[00:29:33] And if we look back historically, we have expanded [00:29:40] and found that there is more to do. There’s new things to do. There’s things that we didn’t fully understand because we were focused on a foundational part. And trying to make that successful. And once that was handled for us, for [00:30:00] example, that freed us up to tackle.

[00:30:04] Other other aspects that we weren’t focused on before. There’s there’s infinite complexity out there of things to look at and things to study and things to do and things to get into [00:30:20] and if we focus too much on a certain task is going to be done via computer and people believe that that’s their value is doing that task.

[00:30:32] It’s going to be scary. Yeah, if we focus on, you don’t have to do that task anymore. We [00:30:40] have other things that we’re going to get into, then it becomes more of an opportunity. And so I think there is a big role of communication, which should be done by positional and actual leaders [00:31:00] who is influencing people to highlight the opportunity that comes from this.

[00:31:07] Alexander: Yeah. You will always have in any size of the organization and because the size of the organization, the more clearly you will see that people that will [00:31:20] more. tend to one or the other extreme. Yeah. So you will have people that are very, very fearful of change and set a highly resistant to change.

[00:31:32] And since you will have others who are very, very opportunistic and absolutely, you know, see the [00:31:40] opportunities of very, very risk tolerant and jump on it straight away. And you need to identify who these people are. It is absolutely crucial because when you at the beginning of the change only talk to the fearful people, [00:32:00] you will not get your things off the ground because all their fear is will do it will stop you in the tracks.

[00:32:09] The important thing is at the beginning of a change, you need to understand where are all the people that have this opportunistic mindset, [00:32:20] that have this very, very high risk tolerance, that jump on these things very, very quickly. Very often these are the people that also understand more about these.

[00:32:32] Yeah. Not necessarily, but very often and because they kind of, you know, know the risks and all these kinds of [00:32:40] different things, but they are just kind of less fearful that they really look for the opportunity. Yeah. And so these will be become your biggest advocates for driving later change and going through this kind of change curve and then convince others.[00:33:00] 

[00:33:00] Chris: Yes. Absolutely agree with what with what you’re saying. I’d like to add on to it that Peter Drucker, like I said, uttered the phrase innovator die really crisp and clear. And that applies to organizations. It applies [00:33:20] to people. So if, if someone is saying, I don’t want to upskill, I don’t want to evolve.

[00:33:30] I don’t want to, you know, learn how to fit into a new way of doing things that might be [00:33:40] Tell you that, you know, they have actually run their course or they’re not going to help bring your future to become normal. So there, there are multiple things that can, can come from this to your point. There is the communicate.

[00:33:59] That how do [00:34:00] we rehabilitate a fear? How do we accelerate an opportunity? There’s different communication there, but there is also understanding how is something going to be accepted? How is a change going to be accepted and and [00:34:20] utilized? So that there can be maximization of value. Because anytime that there’s, there’s fear, it’s going to slow something down or limit or limit something.

[00:34:33] And it’s, it’s relatively close that they share some DNA. With [00:34:40] response versus plan. So, so really more what I should say is react versus plan. React is really a fear based. Hey, you’re forced to do something and you don’t necessarily think about it versus a plan being all right. I have thought [00:35:00] about this.

[00:35:01] And so there can be very plan full. Messages that highlight How we can mitigate fears and maximize opportunities, for example, but in a reactive way, that’s probably not going to be really great [00:35:20] in a plan for way. That’ll be, that’ll be great. So knowing that there’s different types of people that have fear versus opportunity emotions in them.

[00:35:30] There can be a plan of what are the capabilities? What are the user interfaces? How are we rolling things out? And what sequence, [00:35:40] et cetera, to maximize the group of people, the end users that are going to, you know, Experience the change. Yeah. And so just being aware of this can absolutely help with success, but [00:36:00] living in the fear and reactive type of mode is going to truncate.

TO BE CONTINUED…