Adsum Insights Blog

 

With Org Change, Questions Without Answers are Still Important

leadership: delivering operational outcomes

Organizations are constantly making investments and improvements, large and small, to improve results.  

The bulk of these improvements take place within a function.

  • Engineering used to introduce Agile and now AI to improve coding practices. 
  • Marketing lobbies to invest in Data Analytics to improve funnel management. 
  • The Call Center augments their agents or replaces them all together with Agent-assisted AI bots.

Driving overall org improvement by adding up "within function" improvement efforts in a sum-of-the-parts approach makes sense.

The functional leaders seek the investment and have a vested interest in making sure the changes are successfully introduced and adopted because they are often counting on those improvements to help them deliver the numbers they signed up for.

Periodically companies also engage in company-wide improvement efforts.

The objective is to get the whole organization or at least large swaths of it to adopt a particular framework, or system, or to nudge behavior in a certain direction.  The effort affects or attempts to affect nearly everyone.

Efficacy of Corporate-Wide Improvement Efforts

I started wondering about the history and impact of these broad-based organization initiatives and decided to ask ChatGPT to list all the corporate-wide efforts it could find and to rank order them based on their impact on organizational outcomes.  

Major caveats about even the question let alone any answer an AI gives are obviously and immediately needed. 

  1. The question posed is fraught.  What does corporate-wide mean to AI?  My search queries pushed for efforts that touched almost every function in the company or at least multiple functions, such as the previously mentioned process improvement, leadership training, and culture initiatives.  While the AI might be able to find published results, I doubt it could assess how "broad-based" an initiative was in each company.
  2. An impact/ranking analysis like this is going to be limited to and biased by "published" results. There are plenty of companies that engage in broad-based improvement efforts and have no interest in reporting the results.  They may not want the publicity or they may think their successful efforts to improve outcomes for customers might be a source of competitive advantage.
  3. And what results are being published?  Since this is not academic research and more likely business publications, they are likely to be financial results that are being highlighted.  When companies engage in culture change to align employee behavior with key corporate values or the external marketplace, how would we describe and rank order the value of that?
  4. Then there is the whole question of teasing out the impact of any cross-company initiative from all the other efforts inside the company to improve performance.  Satya Nadella became CEO of Microsoft in 2014.  There is no question that he changed the culture of Microsoft. When he took over, the market cap was around $300 billion, and as of early Fall 2025, it was over $3.5 trillion.  How much of that cap change was due to the change in culture vs. changes in product mix, acquisitions, business development, go-to-market, etc?  No one can say, and thus any conclusions about ranking the impact of cross-company initiatives is suspect. 
  5. Any published results the AI finds are likely to be case studies.  You won't find research with some kind of control group, even "yoked-controls" (as was done in the book Good to Greatwhere a company implementing a broad-based initiative is compared to a company of similar size from the same industry who did not take on the corporate wide initiative.  One has to be careful about drawing conclusions from one-offs.
  6. I was sure my AI inquiry would be able to find connections between various types of organizational interventions and positive outcomes.  I am also sure it likely ignored implementation disasters at particular companies. Six Sigma ranks high in the AI summary that follows because it collectively saved companies that implemented it billions of dollars.  But the "B sides" are not hard to find.  Case in point: go find the Business Week article on the implementation of Six Sigma at 3M.
  7. There could be real problems with the differences within and between the 20 initiatives that the AI settled on.  How do all the flavors of culture change, leadership training, DEI, or Team Training get grouped?  Surely some are better than others.  Maybe there should be 40 flavors of corporate-wide interventions instead of the 20 listed here.
  8. AIs do not tell you how they do their analyses.  Heck, the overlords who built them often don't know how they did their analyses.  With a refereed journal, procedures, analytical methods, and references are clearly laid out so that you can critically examine and even attempt to replicate the studies or so you at least know how to better hedge the conclusions.  AIs are a black box.
  9. And, as any good psychometrician knows, you have to have reliability before you can have validity. Are we comfortable we are there with AI's?  I am not sure.  They still hallucinate.  Test-retests are often still recommended as are layered nuanced inquiry strategies. Trying different AIs is encouraged. This sounds more like YMMV...your mileage may vary...than a conclusion you should hang your hat on.

All these caveats make the conclusion so suspect, it's right to ask, "What's the point?"

Because, as you will see in the wrap-up, with organizational change the questions are the point.

 

ChatGPT 4.0 Ranking of Broad-based Organization Improvement Efforts
Tier 1 – Proven, System-Wide High-Impact Efforts
# Initiative Scope Measurable Impact Scalability Cultural Fit Needed Common Use Cases
1 Baldrige Performance Excellence Framework Org-wide Very High High Moderate Public & private orgs
2 Six Sigma Org-wide, Process-level High High Low Manufacturing, Ops-heavy firms
3 Lean Management / Lean Thinking Org-wide High High Moderate Manufacturing, healthcare, services
4 Total Quality Management (TQM) Org-wide High High Moderate Manufacturing, services
5 OKRs (Objectives & Key Results) Org-wide Medium–High High High Tech, fast-growth companies
6 Balanced Scorecard Org-wide Medium–High High Moderate Strategy-driven organizations
 
Tier 2 – High Value, Context-Dependent Approaches
# Initiative Scope Measurable Impact Scalability Cultural Fit Needed Common Use Cases
7 Customer Experience (CX) & Voice of the Customer (VoC) Org-wide High High Moderate Service-oriented, digital-first companies
8 Business Process Reengineering (BPR) Org-wide High Medium High Transformational change efforts
9 Agile & Scrum Methodologies Team-level High High High Tech, product development
10 Cross-Functional Teams & Team Collaboration* Team-level High Medium–High High Innovation, Agile organizations
11 Leadership Development Programs* Org-wide Medium–High High High All industries
12 Employee Engagement & Culture Initiatives Org-wide Medium High Moderate All industries
13 Digital Core Systems (ERP, HCM, SCM) Org-wide High (if integrated well) High Moderate–High Large or scaling enterprises
 
Tier 3 – Innovation & Role-Specific Interventions
# Initiative Scope Measurable Impact Scalability Cultural Fit Needed Common Use Cases
14 Design Thinking Team-level Medium Medium High Innovation, product design
15 AI-Augmented Knowledge & Learning Systems Org-wide Medium Medium Moderate Knowledge-intensive orgs, support teams
16 Diversity, Equity & Inclusion (DEI) Programs Org-wide Medium Medium High All industries (context-sensitive)

 

Tier 4 – Niche, Experimental, or Complementary Approaches
# Initiative Scope Measurable Impact Scalability Cultural Fit Needed Common Use Cases
17 T-Groups (Training Groups) Team-level Low–Moderate Low High Leadership development, OD settings
18 Servant Leadership Philosophy Org-wide Medium Low Very High Values-driven cultures
19 Corporate Innovation Labs & Hackathons Team-level Medium Medium High Innovation teams, tech companies
20 Holacracy & Flat Structures Org-wide Mixed Low Very High Experimental or flat orgs

 

Other Ways of Grouping the Interventions

In addition to the impact tiers here, there are other ways to group the organizational improvement approaches.

Centralized, Tops-Down vs. Decentralized, Bottoms-up. Centralized, Tops-down approaches are directed, non-optional efforts. An example would be Digital Core Systems initiatives like ERP implementations. Functions usually aren't given to choices to not use the system.

Other examples would include deciding to apply for the Baldrige Award or ensuring all leaders were trained in a certain methodology where their progress and results using the new methods were tracked centrally.

Decentralized, bottoms-up improvement efforts are approaches where people throughout the organization are given the tools and it is up to them to decide how to leverage them. 

Leadership training is the best known example of decentralized, bottoms-up improvement. Leaders are often given a range of tools from strategic thinking to values training to people development approaches to "ways of being" ideas on how to "manage self" more effectively to improve results.

In most of the leadership training roll-outs, there is no real central project plan or central tracking of results, other than to try to "get everyone through it."  Leaders take what they learn and are empowered to figure out how to implement in their environment.

Well-defined vs. Less Well-defined.  Another dimension you could organize these 20 approaches by would be from well-defined to less well-defined, bordering on squishy.

You can disagree, but in my view applying for the Baldrige, implementing Agile and Lean methodologies, and ERP roll-outs are well-defined broad-based initiatives.

On the other hand, DEI, AI-augmented Knowledge and Learning Systems (I believe these will get more structured, but they are too nascent at this point), and Holacracy are less well-defined. 

Therefore, if you buy ChatGPTs ranking of impact presented here, then, as would be expected, more well-defined, tops-down initiatives clearly have more impact. 

And that, ladies and gentlemen, is the most obvious statement you will read for months. 

So what then?

These are questions which need to be answered even though clear empirical evidence is often lacking.  Not asking the questions is in effect answering them.

Broad-based Initiatives or Not?

Like a boxer's left jab sets up the straight right, you can just consider this initial inquiry as a set-up the more important follow-on questions.

In your own company or in organizations you work closely with:  

  • Is the organization engaged in any corporate-wide improvement that is impacting or trying to impact how almost everyone in the company works or behaves?
  • If yes, are any metrics being used to assess progress and impact? If not, should there be?
  • If there is not an effort that would be described as organization-wide, do you think there should be such an effort?  What employee, customer or shareholder outcomes do you think the organization would achieve from such an implementation?
  • If you think they should be pursuing a broader-based initiative, why do you believe they currently are not?

These are questions which need to be answered even though clear empirical evidence is often lacking.  Not asking the questions is in effect answering them.

 

In Part 2, I will examine some of the broad improvement efforts that surveyed HR leaders said they are considering in 2025.

 

Dennis Adsit, Ph.D. is an executive coach, organization consultant, and designer of The First 100 Days and Beyond, a consulting service that has helped hundreds of newly hired and promoted executives get great starts in challenging new jobs.