Fixing Decision Latency Before Transformation Stalls With IDEA Consulting Experts

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[00:00:26] Why do major transformation programs stall even when the strategy looks convincing and the technology is ready to go? Well, in today's episode of Consulting the Future, I'm going to be joined by Dr. Kobe Glass of IDEA Consulting Experts. And he's going to explain today why the hidden problem is often the operating model underneath.

[00:00:53] And he's going to be drawing on over 20 years of work with distressed programs and how he looks for aging decisions, governance meetings that produce reports instead of action, overloaded teams, portfolios where everything is treated as a top right, and portfolios where everything is treated as the top priority. I suspect that everybody listening there has encountered more than a few of them in their workplace.

[00:01:20] So I want to discuss his 24, 48 and 72 hour decision spine. Why the first 30 days of stabilizing a troubled program. The first 30 days of stabilizing a troubled program and why 100% utilization can reduce throughput.

[00:01:43] And Kobe will also offer a timely warning around how AI can accelerate whatever system it enters at machine speed. And by that, he means everything from broken processes and unclear ownership. So if your transformation is busy, but not moving, hopefully today's conversation will help you find where the work has actually stopped. But enough for me. Let me introduce you to him now.

[00:02:12] So thank you for joining me on the show today. Can you tell everyone listening a little about who you are and what you do? Yeah, thanks for having me, Neil C. Hughes. So I'm Dr. Kobe Glass. For more than 20 years, I've worked in a transformation space. I come into distress programs, distress transformations where strategy is not translating into execution. And I step in and help stabilize the program first. That is what I built my reputation on, stabilizing a program.

[00:02:40] And from there, we would design an operating model that supports the flow of work to move the organization forward. So I've been doing that the last 20 years. Prior to that, I was in the military as a submarine nuke officer. So again, my mind is always organization design and strategic systems. And I've got to ask, looking at your origin story there, submarines to big tech. Is there a story there that made you go from one to the other? There's got to be, right?

[00:03:09] So the story for me, Neil, is I come from a military family. And at the time, I had an uncle that was a nuke in the Navy as well. Liked a lot from him through mentorship. And just explored my curiosity, right? So it was like, hey, I started setting my mind and my goals on that around the age of 15. And we made it come into fruition. So again, it was all from the support and the influence around me. Love it.

[00:03:35] As you said at the beginning, you've had 20 years in the tech industry and probably seen a lot of big changes and transformations from the internet to cloud and mobile. And now, of course, AI, which has completely changed the game. There's never been more tech in our lives and in the workplace. So one of the things that stood out to me about you is I was reading that you argue that enterprise transformations now rarely still because the strategy or technology is fundamentally wrong.

[00:04:02] So if the real problem is the operating model underneath, what are the real warning signs that tell a leader that their transformation machinery just isn't working? What are those early signs? Yeah. So, Neil, one of the things I look for is I look for friction rather than failure to start, right? And five typical symptoms usually emerge, right? Is decisions aging, right? If decisions are aging, that is where the funnel stops.

[00:04:32] Because one, if we can't move forward without a decision and it just sits there in an age and age, that is a symptom of an operating system problem. So usually we start mapping that backwards and try to figure out, hey, who owns these decisions? And when you start that conversation, most times teams know like they have a problem and what needs to happen. But nobody owns the decision to unblock the teams.

[00:04:55] The other aspect is when governance meetings produce reporting rather than decisions, right? So I got this thing I call governance theater. And this is where organizations spend so much time describing a problem versus fits in its current state. The other symptom is work accumulates. Everything is priority number one. So all the work is context switched.

[00:05:22] You have one engineer working across five different initiatives and you wonder why things are not getting done. Then I take a step back and I look back, how much work do they actually have in flight? Like, and that tells a big story. You have a portfolio of 40 programs and all 40 programs are in flight at the same time with the same body of resources. Then I go back and I look at how do capacity choreography happens?

[00:05:47] And what I mean by that is, hey, what are our top five priorities we should be working on and who are working on those priorities? And then when you look at the mixture of divide and conquer between the entire organization, that supports why your whip is not throttle because you don't have whip limits. So it's so much work in flight. So those are the five friction points I look for up front. And I typically try to make those visible to the client very up front.

[00:06:14] So it's like, hey, we're not here to come ask questions of who is failing. We're trying to see why work has stopped flowing. That is my point. And there are a few echoes of analysis paralysis as well that we've all seen and heard in the workplace. And you describe this, a decision latency as one of the hidden killers of transformation. I love that line.

[00:06:36] And when I was researching you online, one of the things I was reading about is a case where three decisions sat with a CEO for 18 days, which eventually contributed to the collapse of a $72 million portfolio. So why are organizations so bad at making decisions at speed? And how does your 24, 48, 72 hour decision spine, how does that change this? Yeah.

[00:07:03] So the ambiguity in making decisions truly sits at one is it's agile, right? We all know there's no working, right? And then we talk about, hey, the team should have autonomy to make decisions. And that is necessarily true. But the decision types should be assigned as part of decision rights. Is this an operational decision? Is this a tactical decision? Is this a strategic decision? All right.

[00:07:32] And we break that down in those three categories. If this is something tactical, this means the team can handle this. And this should be resolved in 24 hours. If this is operational, yes, maybe the team can handle this. But this also requires some leadership intervention. And it should be one person from the leadership team that owns the decision and move the team forward. That should happen in 48 hours. And 72 hours will go in for strategic decisions.

[00:07:56] Something that has impact strategic initiative, P&L, that should happen within 72 hours. So I had this one case now. I was looking at a $72 million portfolio and the organization thought they had a delivery problem. So we sat down and we started to trace the work backwards. And doing that, something interesting emerged.

[00:08:20] That decision, three decisions across three portfolios, was sitting on a CEO desk for 18 days for something that takes less than 72 hours. So we had what we call intervention. And intervention within a 60-minute conversation, we got the decisions needed to unblock the portfolio. In that particular use case, you know, hundreds of team members was downstairs working, doing activity,

[00:08:48] but the system was officially stopped. They could not move forward. So you talk about waste of dollars and resource time. Is that CEO still in a job? I just don't have interest. CEO still has a job, right? And in fairness, right, even inside of their operating model, the CEO operated on a different cadence of approvals from what the business needed to move work.

[00:09:17] The CEO is operating on a quarterly basis, and the business needs to operate on a weekly basis to continue to move this work. So you had two systems out of sync, and that's why the work wasn't moving. And if we were to look inside any large organization, I think most large transformations come with steering committees, dashboards, status meetings, layers of governance, and so much else goes on there. A lot of red tape as well.

[00:09:44] But you said a few moments ago you warned about governance theater, which I think everyone would have seen as well. So how can leaders tell when governance is protecting the business versus becoming just part of the problem? What should a useful governance meeting actually accomplish without slowing things down? Yeah, so John, Neil, walking outside of any governance forum, a governance meeting should produce decisions. It should produce escalations. It should remove blockers from team.

[00:10:13] And I should leave that meeting knowing what has changed because that meeting happened. That meeting should not be happening to pretty up a PowerPoint slide. The meeting should be happening to unblock teams by producing decisions, resolving those escalations, removing those blockers so that work can actually flow. So that's why I elevate and say, hey, governance is theater. It's when so many executives spend time inside of steering committees, looking at the PowerPoints.

[00:10:42] This doesn't look as red as that one, but it's still orange. So let's call it orange. They're describing a problem in a better way that they're using their talent to actually fix the problem. And I was also reading that when you arrive at a distress transformation, you advocate stabilizing before transforming. So I've loved to try and bring that to life.

[00:11:03] Talk me through those first 30 days when you stop, measure, expose, and prioritize before deciding whether that program should go ahead and continue at all. What are those 30 days like? Yeah. Yeah. So in the first 30 days for me, day one, I'm sitting down with the key stakeholder, which is going to be a C-level executive that owns the decision, which is usually my sponsor. And day one, we stopped the bleeding. We published the decision spine. We set the 24, 48, 72-hour rule.

[00:11:33] Each decision has a named owner. And each decision has a trigger escalation point that if this doesn't happen within this time frame, it escalates to the next peer above, which is usually the next C-level. The CTO or the CEO or CEO, because again, decisions is what stalls the work. Day 10 and day 10, second weekend, the second week, what we should have now is a kill list. A kill list means that we have looked at the portfolio.

[00:12:02] We understand where work has become a distraction and doesn't contribute to the strategic initiatives of the program. And we're going to kill that work. That work stops. We move that capacity to the highest value work so that we can get flow established for the work we need to get out the door. By day 15, by day 15, we have set WIP limits across the entire value streams so that we can control the work that's in progress.

[00:12:30] Because one of the hardest things I have explaining to some of the executives I talked to is 100% utilization does not equal maximum throughput. So that's one of the hardest conversations. And to get that point clear is we set WIP limits so that we throttle the amount of work that's in flight so we can focus on getting work done. And by day 30, this is a go and no-go decision. So most strategy orders and bit tech consultant is going to bring you a strategy deck on day 30.

[00:13:00] On day 30, for me, that's a decision point for the organization. Now that we have the program stabilized, do we retain your service to build the operating model that it's going to take us to run? And in those next six months, we focus on building and installing the operating model that it's going to take the organization to run even without me once I'm gone.

[00:13:21] And there's also a counterintuitive idea in your work that running teams at 100% capacity can actually make delivery slower. So you've seen teams reduce work in progress and dramatically improve lead times without adding people. So what does less allow organizations to accomplish more? Why does that happen? And how do or how should leaders decide what gets stopped? Yeah.

[00:13:49] So in that example I gave you about the CEO that had those three decisions sitting in a $72 million portfolio. What we did, John, within those first 30 days, what happened was that the cycle time went from 18 days down to 15 days, which means the teams were getting faster. And then the lead time went from 22 days down to 14 days. That is by implementing decision control and real governance that produces those things we talked about.

[00:14:18] Decisions, escalation, remove blockers so that the team can move. That didn't happen because we made people faster. We didn't go out and make them do sprints till they got faster. No, that happened because we created a system of flow so that the work flowed better. That's how that happened. Love that.

[00:14:36] And when I was doing a little research on you, I also read that you've led major SAP and AWS programs where there's often enormous attention on whether the tech is ready for migration or cutover. So what have you found gets overlooked on the organization side? And what should executives verify before believing a green technical dashboard means, hey, business is genuinely ready to go? Because it's often not that simple, right? Yeah.

[00:15:04] So across those programs I've been in, you know, AWS, SAP, HANA, all of those programs is one of the things that I always try to stress is that technology readiness does not equal organization readiness. The system can be technology equipped and ready to go live tomorrow. But tomorrow, the organization is not ready to absorb it.

[00:15:30] So that's the distinction we have to make as an organization. We have the technology, which means, hey, the strategy is there. But the piece that sits between that strategy on paper and the strategy actually working is the operating system. And when you have the operating systems in a way that it governs the body of work to produce flow, produce decisions and cut the flat, that is when you have organization readiness.

[00:15:56] That's the capability of the people and the systems working together, not just the technology. And a question I'd love to ask you here is AI is now being inserted into many of the transformation programs with huge promises of greater speed, better productivity, etc.

[00:16:14] But if an organization already has slow decisions, poor processes, unclear ownership or overloaded teams, could AI run the risk of just accelerating that level of dysfunction? And if it does, what operating model needs to surround AI for productivity gains to translate into very real business outcomes? Is this something that you see? Yeah, so Neil, you asked a very good question at a real eminent point in the tech space right now. Absolutely.

[00:16:44] AI is an accelerator. And as an accelerator, AI does not distinguish between good and bad systems. If you have broken processes and you add AI, AI accelerates those broken processes. If you have unclear decisions and you insert AI, AI accelerates the ambiguity. So yes, AI is an accelerator. So before executives ask, where do we put AI?

[00:17:13] They should ask, what are the decision systems surrounding AI? So it's all about that ecosystem of decision system. Because again, there's a human intellectual side of this and there's the artificial intellectual side of this. So there always got to be a decision point that bridge to human judgment before the accelerator would ever produce the outcomes that you're looking for. So you also, I was reading out of a useful question for leaders, which is where is work actually getting stuck?

[00:17:42] And if someone listening suspects their transformation is losing momentum right now, how can they distinguish between a technology problem, a people problem, an operating model constraint or something else? And what should they measure first to find that real bottleneck? Yeah. So what we would usually do is find one important outcome that landed in an organization. Then we would trace that word backwards. And one thing is always relevant in that trace back backwards, Neil.

[00:18:12] We discovered that work somehow slowed down, stopped or stalled at one point in time. And that's where you measure. In today's organization, organizations have thousands of activity metrics they measure. But rarely do they measure where does the work stop or how long does a decision sit still? And usually when you land, eight times out of 10, it's a decision somewhere in that pipeline that's thrallowing the work. Wow.

[00:18:41] I think that's a powerful moment to end on. And for anybody listening that would like to find out more information about anything we talked about today, especially if a lot of the examples resonated with people listening, where should they go? Yeah. So the best way to find me and my team, Neil, is on LinkedIn, linkedin.com slash Kobe M Glass. We post insights daily to daily transformation tips. And also you can look us up at www.getideaos.com.

[00:19:10] If you're dealing with a transformation distress program, you can go on the website and fill out a diagnostic request. In complimentary, I'll review that with you. And usually in all these conversations, we walk away with five of those symptoms we talked about earlier, Neil. And I can tell you where to start to stabilize your program. I love it.

[00:19:29] And one of the big lines that came out from listening to you today was the fact that decision latency can quietly kill large-scale technical rollouts long before the strategy itself fails. If those words resonate with you, please, I urge you to check out my guest today. I'll leave all the links to everything that you mentioned there, Kobe. Anyone listening, I'll point them in your direction. But just a big thank you for talking about all this in a language everyone can understand,

[00:19:56] because so much of what you talked about could be found in just about every workplace on your side of the pond and mine, 5,000 miles apart. But thanks for sharing that today. All right. Thank you so much for your time, Neil. I think Kobe's message today is that transformation recovery begins by making friction visible. Yep. Track how long decisions sit. Name the person who owns each one.

[00:20:24] Limit work in progress and make every governance meeting. And ensure that every governance meeting produces a decision, escalation or removed blocker. And I think that 24, 48 and 72 hour framework, easy to remember, but it also exposes whether leadership cadence is matching the speed that the business requires, especially in this fast moving AI world that we find ourselves.

[00:20:51] And the same discipline matters when AI enters the program, because faster technology cannot compensate for an operating model that keeps waiting for a direction. So a big thank you to Kobe for giving us a practical way to diagnose stalled work before another strategy deck is commissioned. And you can find his daily transformation insights on LinkedIn.

[00:21:16] Maybe even request a diagnostic at get over on his website. You'll find all the links on Tech Talks Network on a blog post associated with this episode. But over to you, where is work currently waiting inside your organization? And which decision would help you release it? Let me know again. Let me know. TechTalksNetwork.com Love to hear from you on this.

[00:21:43] Remember, there are nine different podcasts, 4,000 interviews over at Tech Talks Network. Hopefully, I'll get to see you all over there. Speak to you soon. Bye for now.