When is the Right Time to Re-evaluate Your Strategy Planning Process? Transcript

Ross Martin:

Yep. And as you said, it's now become necessary to include those roles, those leadership roles around both digital and physical risk management in all of your strategic planning and execution going forward. They can't just be somebody that you talk to after you've figured out what your strategy is. Our next topic is, when is the right time to reevaluate your strategy planning process within, say, your fiscal year? Idris, would you like to take a first swing? Sure, sure.

Idris Manley:

Yeah, I know. You know, as a PMO leader, I certainly would advise companies to begin as soon as possible. But that's probably not realistic, right? As soon as possible would be as soon as you completed your planning cycle to then review improvements you can make. But the reality is, I think, you know, after people have spent, you know, the time that they have on planning, they probably want to take a break. And usually then it's the holidays and, you know, near the end of the year, etc. But I do think it's important to think about or start having those conversations at the beginning of the year. That gives you, you know, if you're on an annual or calendar cycle, then more than likely by June, you're kicking off. officially, uh, your planning cycle. Uh, and so having that first six months from, from January through June to really begin thinking about what went well and what you can do to improve, I think it's critical. But the reality is that most, many companies don't even think about how to improve. They just continue to plan and execute in the way that they had the previous year without little to no change. And, uh, and that can certainly influence or impact their results.

Ross Martin:

At my media company, we finished our annual planning process in, say, September, October timeframe, rolled into the annual budget process, and then kicked off the next calendar year. We had a number of things we wanted to do differently for the following year's strategy process, which was to kick off around June, like you said. And one of them was that we really wanted to adopt a new tool to do it. It was still pretty much Excel and PowerPoint the previous year. And so there was a desire to really up-level that sort of thing. But as you well know, as a PMO leader, it takes a while to implement tools. And we began the selection around January, February time of the tool. We started trying to implement it around like April, March, April. Basically, the net on that is we couldn't get it done in time because we had to get going on the strategy process in June. And we weren't ready with the tool because we didn't start early enough. And we ended up using Excel and PowerPoint again and again.

Idris Manley:

Yeah, yeah. No, I think that it's really important to understand if you can get ahead of that, right? If you can start to think about that as soon as you finish up or wrap up the previous cycle, then that helps you certainly get ahead of that. But back to the original question, I think it's really important for someone to be designated as a person that can objectively evaluate based on the results of the previous cycle, are there improvements or changes that can be made to how we are strategizing, how we are planning, whether it's accounting for certain roles that maybe weren't contributing to the previous discussion or functions, whether it is being able to, maybe it's time to get a facilitator. You know, the conversation that we had previously, we just weren't able to iterate and get to the real value of what we needed to be able to come to reach the right conclusions or right understandings and maybe having a third party or an objective person that can help facilitate and help everyone really contribute in a way that the company can really benefit from the collaboration.

Ross Martin:

One of the things that impacted us in at least two companies I've been at is turnover. So the reality is, is that the person who drove the strategy planning process had some good ideas of what they wanted to do differently the next year, but it wasn't them. And so the new person comes in and they change all sorts of things around. In one case, the entire sort of structure of how we gathered our strategic objectives and then broke those down into different types of initiatives and then worked to figure out what were going to be the projections around the kind of cost and revenue to be associated with some of those things. was totally different than the year before. And many of the business leaders were flummoxed, to use a good word, about that because they were confused, even though in a lot of ways, it's all there's many different frameworks, but in a lot of ways, they're all the same. Yeah. And and yet it would have been better, I think, in that case to just stick with last year's wording just to keep people from getting confused.

Idris Manley:

Yeah, that makes sense. I think another interesting change that we'll be seeing or continue to see in strategic planning and when it's performed is really around AI. And I suspect that a lot of companies, as part of their strategic planning, they're starting to discuss what their objectives are for the year. And I think it's going to look a little different than some of the other initiatives and projects because there's so many things that are unknown. There's so much information. So really even being able to decide what is an ideal or an optimal goal to set for the year is probably going to be a lot of different opinions and concerns around that. So it'll be interesting to see how that

Ross Martin:

It will be interesting. I also see it as like, you know, some people within the company are going to be understanding and on top of what's going on with AI in their area and others won't. And I wonder, you know, I sort of expect that CTOs and CIOs are going to be expected by their company to sort of tell everybody about how AI should work in their different areas. But the reality is, is, is the, you know, the CMO and the chief product officer and all of them should be thinking about it for their area, but then working closely with the CTO and CIO and the CISOs to, to really be thoughtful and careful about what, what even is allowed at this point because of, you know, the security issues.

Idris Manley:

And to be realistic, I mean, the realities I was reading somewhere that said that more than 70% of AI projects fail. The number may even be even higher. And so when you look at sort of that failure rate, it's really important to define those projects in an effective way where you're being realistic. realistic about your data that you have available, the quality of that data, realistic on what you can achieve based on that, realistic about your culture. There may be people that are fearful of AI and maybe aren't really motivated or excited to be able to support and ensure that initiative is successful. So I think there's a lot of variables that should be taken into account other than just the executive saying that this is what we want to accomplish if they want to ensure success.

Ross Martin:

Well, and we were just talking earlier today about how AI initiatives inside companies are not going to be exactly like your product and feature set type initiatives. They're going to need to be run slightly differently and much more data driven, still agile, but different. Yeah, absolutely.

Idris Manley:

I know. I mean, With traditional project delivery, it's usually around delivering features and functions and capabilities, as you mentioned. But when you realize that AI is really anchored in data, and your outcomes of your AI projects are only as good as the data that you have, then you have to really reorientate yourself and your thinking and your mindset around what's important. And the reality is that when you're talking about data, you're, again, you're not talking about features, but really how do you iterate through that data to give you the insights that you need to be able to allow you to take the actions that you would like. And that normally will be an iterative process where you will have to continue to scrub and cleanse and maybe integrate new data sets and continue to iterate through that process to be able to get to a point where that data is actually what you need it to be in order to empower your AI initiatives.