BEYOND THE HIERARCHY

THE RESEARCH

Basis of research

This White Paper is built on several years of research including:

In-depth interviews with over 150 employee innovators who have successfully driven innovations from within mostly large, established organizations
Conversations on the topic with about 100 heads of strategy of mid-to-large enterprises, primarily members of the Outthinker Strategy Network¹
A series of panel discussions we organized around this topic incorporating about 25 senior corporate leaders
Interviews with about 20 of today’s leading authorities on the topic of organizational strategy and innovation, including:

Secondary research on Haier’s RenDanHeYi model and first-hand interviews with experts on the model, including:

A quantitative survey of about 500 mid-level managers with decision-making authority inside primarily U.S. companies

Summary of findings

From Internal Innovator Interviews: Seven Barriers

Over the course of several years, we started to look closely at the experience of employees seeking to innovate from within traditional bureaucracies. We eventually interviewed over 150 internal innovators.

Through these interviews, we found that:

This path of self-directed, employee-generated innovation has historically been far more prevalent than we understood. Indeed, innovative ideas from employees have done more to shape society than those of entrepreneurs.

With remarkable consistency, the 150 innovators, when asked what they saw as barriers to driving internal innovation, named the same seven key problems.

A set of emerging concepts precisely address these seven barriers, opening up a pathway for internal innovators.

Far more is known than many realize about what it takes to unleash the potential of would-be internal innovators.

A few organizational principles, when introduced, could have the potential to remove barriers to internal innovation. It is these principles that we plan to highlight and explore in this White Paper.

We asked each of them: “What, in your experience, are the biggest barriers to driving an innovation from within?”

Once we collated all their answers, we realized that they clustered into seven clear groupings. Together, the employees and innovation experts repeatedly mentioned these seven barriers as the most common challenges to internal innovation. We also realized that, if we turn those seven barriers around and look at the obverse, we see solutions that organizations can introduce to remove the barriers.

The list below reflects the barriers we found, in an order of the natural sequence by which internal innovators tend to face the most common barriers. We gave them names that form an acronym (IN-OVATE) that hopefully make them easy to remember.

I

Intent

Facing early obstacles, many would-be internal innovators abandon their original intent. They eventually simply give up looking for chances to innovate. Successful ones dig deep to keep their intention alive and, as a result, are more likely to spot innovation opportunities.

N

Need

Most employees do not understand what kinds of innovations their organizations need. Want proof? Fewer than 55 percent of middle managers can name even two of their company’s top strategic priorities.² So even if someone is inspired to look for new ideas, they look in the wrong places and then propose ideas of little strategic value. Successful ones take the time to learn critical market forces affecting their company, understand what their organization cares about, and sense unmet customer needs.

O

Options

Would-be internal innovators often grow frustrated because they become fixated too early on a few innovative ideas—or even worse, just one. It’s much more strategic to continually generate a flow of new ideas and manage them like a portfolio of options.

V

Value blockers

It is commonly accepted that innovative ideas are inconsistent with, and therefore disruptive to, a company’s current business model. The organization appears to raise value blockers that inhibit an appropriate new business model from forming around the new idea. Successful innovators find clever ways to engineer their ideas so that rather than conflicting, they enhance the company’s standing.

A

Act

Established organizations tend to ask employees to prove an idea will work before giving permission to take action. This puts would-be internal innovators in a fatal Catch-22: they can’t take action so they can’t prove their idea will work so they can’t take action. Yet most new ideas are better suited to the opposite approach—taking action in order to prove the idea—and successful innovators devise ways to do just that.

T

Team

Corporations hamper internal innovation by the nature of their structure: They use siloes hierarchies, act slowly, and value results over learning. Successful innovators recognize that pursuing new ideas often requires the opposite, and so they pull together a cross-silo team that runs at a rapid pace and is geared toward learning, rather than delivering results.

E

Environment

Getting support for new ideas is politically complicated because the leadership behavior, types of talent, organizational structures, and cultural norms that help established organizations sustain their core operations also tend to hinder internal innovativeness. Successful internal innovators figure out how to find “islands of freedom” from which they can access the talent, structures, cultural norms, and leadership support that support attempts at innovation.

From Expert Interviews: Guidelines for Engaging in Ecosystems to Maximize Value Creation and Sharing

As companies move away from traditional industry chain models toward operating within ecosystems, their internal organization are also evolving into forms that look more like ecosystems. This is caused by the fact that ecosystem-based competition is shifting the sources of competitive advantage. These are the key insights drawn from expert interviews.

1

Ecosystems are not new (Heinz and other CPG products, airline alliances, IBM-Intel-Windows, Sun Microsystems’ are some examples) but they are increasing in importance. This growth seems due to various causes.

Digitalization reduces transaction and coordination costs/effort (and increases speed) making collaboration between firms a better choice than alternatives (such as the firm delivering entirely on their own or the customer engaging independently with multiple firms).
Digital components of a value proposition mean that one firm is less likely to have the complete solution (digital leads to modularity). Firms are sticking more closely to their core and letting partners manage the ancillary parts.
Globalization implies firms must offer different variations in different regions to address different national needs or technological resources. Growing interdependence across industries or regions leads to a bias towards partnering vs. owning. (Knee, Gomes)

2

The advantage of delivering a value proposition through an ecosystem (or “constellation” or “alliance” of “business combinations”) comes about when the end-user value proposition is best delivered by a collection of players, rather than just one or a few. The more players required to deliver the superior value-proposition, the more attractive an ecosystem becomes (v. delivery by a single firm). When the players needed offer complements, rather than components, the case for an ecosystem becomes even more compelling. (Bova, Knee, Gomes)

3

It is critical that ecosystem players are able to coordinate themselves effectively. This is what Ben Gomes calls “1 + 1 = 1” meaning individual organizations when forming an alliance, merger, or joint venture must be able to “integrate and work well together as one.”

The ultimate value you deliver to your end-user, being composed not of just one product and/or service, but of a combination of products and/or services each delivered by a different stakeholder, requires that one can coordinate this multiple stakeholders. But such coordination is not easy to facilitate, especially the greater the number of players. Some keys to doing this well include a) ensuring interest alignment upfront, b) APIs, c) standards, and d) mechanisms specific to the industry.

Managing the ecosystem players is hard work and takes skill that builds over time. (Gomes, Nolan)

4

Scale is still the primary source of advantage. There are two sources of scale: economic and network effects. Network effects advantages are (perhaps) the more important source of advantage for ecosystems and they are often misunderstood. For example, neither Netflix nor eBay have network effects because customers do not interact with each other. Traditional cost-based (economic) scale advantages accrue to individual players in the ecosystem and can increase their bargaining power. (Knee, Gomes)

5

When scale advantages are best shared, such activities may become shared “utilities.” For example, a group of firms share a bundle of resources that are not owned by the same parent company (independent or interdependent). These can be organized in different ways. One new phenomenon for organizing these are platforms. (Knee, Gomes, Nolan)

6

The more permutations of the value proposition, the higher the minimum scale requirements are. Advantages from network effects are more valuable when the end value proposition is more complex and so offers more personalization options. For example, Uber or Lyft offer few permutations and so less personalization opportunities. AirBNB offers many. So it takes less scale to compete with Uber than AirBNB. (Knee)

7

If an ecosystem’s players have a predilection to stay (i.e., player captivity), the ecosystem becomes stronger. Players may stay because (a) of switching costs or (b) because they are better off staying than leaving.

Switching costs can come about because of a gatekeeper (e.g., Apple), because you have to design your product to fit (e.g., a standard), because you adjust your operations to fit (e.g., airline rout systems fit tightly), or other reasons. Players stay voluntarily when they get more value out of the ecosystem than out their alternative (what Ben Gomes refers to as 1 + 1 = 1.4 + 1.6 and what Felix Oberholtzer-Gee says comes from improving the Propensity to Sell or what we might call Best Alternative to Ecosystem Participation).

When someone extracts more value than they add, the ecosystem becomes unstable because the division of value does not pass a “fairness law,” as Gomes calls it, or, at the extreme, other player(s) is(are) losing value by participating (they are adding more value than they are extracting).

Some ecosystems are exclusive (high switching costs) and some are open (e.g., Lyft v. Uber, eBay). There seems to be a philosophical divide between the two. (Knee, Gomes, Oberholtzer-Gee, Nolan)

8

The combination of players must create value, what Ben Gomes calls 1 + 1 = 3. Be selective when you add a player because each time you add one, it increases complexity. Some examples of value include: More scale? A more complete product? Reaching more markets? More agility to change? Network advantages? (Gomes)

9

Value extraction, or value share, by players is critical. How much value you are able to extract depends on perceived bargaining power, which is why a new ecosystem creator may build ecosystem partners over time, as the value of their ecosystem and thereby their bargaining power grows. For example, a gaming platform or app store building developers over time. Partners are never true allies, they are “frenemies” engaged in “coopetition” and it’s helpful to think of them in this way. (Oberholtzer-Gee, Bova)

10

If an ecosystem’s end-users have a predilection to stay (i.e., customer captivity), the ecosystem becomes stronger. End-users may stay due to (a) habit, (b) the superior value they receive (which comes from what Felix Oberholzer-Gee calls increasing the Propensity to Buy), (c) switching costs, or (d) high search costs. (Knee)

11

Digital aspects of the value proposition tend to reduce player or end-user captivity. APIs reduce switching costs for players and end-users. Digital interfaces make it easier to overcome end-user habit barriers (e.g., one can create an interface that looks and feels close to a competitors’). Digital search reduces search costs. (Knee)

12

To decide if you want to engage in any ecosystem, first ask, “to what extent does your success depend on working with other players?” It’s important to ask “what value do I bring to other players” instead of only on the value you gain. (Gomes)

13

In thinking through the design of an ecosystem, it helps to start with the customer: Ask what do they want and how do they want to buy, then identify what “parts” you can deliver and which other players should deliver. Think about what components are valuable, who you need in place (e.g., do you need a brand, technology, standards) and which of these can you best deliver and which are better delivered by others? (Gomes, Bova)

14

Then choose the relationship with these other players: simple complement (user buys each separately), JV, partnership, platform, etc. (Bova)

15

This requires a mind-set shift. First, shifting from thinking about an alliance, or a set of alliances, which is natural for leadership, to a partnership “program” that many can join. It’s one thing to manage a few alliances, but then you reach a point when you say “we have many alliances, how do we manage this?” The second mind-set shift is from wanting to control to relinquishing it and being comfortable with that. (Bova, Gomes)

16

One can think of the ecosystem as an “extended” enterprise. (Gomes)

17

Whether there will be one, a few, or many ecosystems (fragmentation of ecosystems) depends on factors such as scale advantages of ecosystems, industry structure, and network design. (Gomes, Knee)

From RenDanHeYi Expert Interviews and Secondary Research

The secondary research we reviewed (about thirty papers in all) and expert interviews we conducted provided a fascinating view into the RenDanHeYi model. While they revealed numerous insights, those that were most directly relevant to this research study were that several unique characteristics distinguish the RenDanHeYi model. While there is no clear definition of RenDanHeYi, one can say that these elements would form the basis of such a definition:

1

Treat employees like intrapreneurs.

2

Collaborate with ecosystem partners to deliver value to end users, conceiving the market as an ecosystem rather than the more traditional linear industry supply chain.

3

Work in smaller independent units (Micro-enterprises for “MEs”) rather than traditional business units

4

Empower MEs to operate with considerable autonomy, letting internal marketplaces drive funding rather than using a centralized command and control approach in which a central authority reviews BU performance (e.g., annual) and makes staffing and budgeting decisions

5

Emphasize a closeness with end-users (what Haier calls “Zero Distance”) to enable MEs and intrapreneurs to more quickly spot emerging trends rather than have such trends tracked centrally by, for example, competitive or customer analytics teams

6

Use mechanisms to make it easy to intrapreneurs to get the resources (funding and time) to pursue new opportunities, following a philosophy that allows employees to try and fail, rather than defaulting to standard business case proposal reviews

7

In perhaps the most interesting and radical characteristic of the model, give MEs an option to choose which support services (e.g., R&D, HR, finance, IT) to use. In hierarchical models, business units are forced to use the shared services provided by the company in order to create scale cost advantages. But for reasons described below, it is now possible to economically deliver shared services as lower scale.

As you can see from the table below, these characteristics of the RenDanHeYi model help address the seven barriers our research shows employees most commonly face when seeking to drive innovations from within.

From Quantitative Survey of Mid-Level Managers

The recognition that the key elements of the RenDanHeYi model represent a set of organizational principles that collectively address all seven of the barriers employees most often face when seeking to innovate from within suggests that introducing these principles should, in theory, unlock internal innovation from employees which, in turn, would ideally result in improved performance of the firm.

But does it?

We found numerous papers that offered a logical argument for why this should be and case examples that illustrate this to be true, but to our knowledge, no systematic study supports such logic to be true or such cases to represent a norm.

As such, we conducted a survey of nearly 500 mid-level managers with decision-making authority, covering companies across a range of industries, primarily in the United States. We asked three sets of questions, totaling eleven in total:

Input questions related to organizational and strategic choices a company and/or its leaders can directly influence that could drive performance. In our case, we specifically asked questions that were identifying by expert interviews as the most important unique defining aspects of the RenDanHeYi model
Output questions relate to actions and behaviors that the input choices produce. In the case of our research, we specifically sought to measure Entrepreneurial Intensity (EI), described in the box below.
Result questions related to outcomes that come about from the output (in our case from EI). We specifically sought to measure the resulting impact of inputs and outputs on (a) the ability of firm to recruit and retain top talent and (b) the financial performance of the firm relative to competitors.

In other words, inputs drive outputs which, in turn, drive results as the diagram below illustrates.

Input choices (e.g., organizational, cultural, and leadership)

Output choices: behavior induced by input choices, in our case specifically, EI

Performance that results from higher or lower levels of EI (talent recruitment and retention, financial performance)

Entrepreneurial Intensity

Entrepreneurial Intensity (EI) is a well-adopted measure of the level of entrepreneurial behavior in an organization. It seeks to address limitations of the broadly known Entrepreneurial Orientation (EO). EO focuses on the occurrence of entrepreneurial actions within an organization across two dimensions: how often the company engages in such events (frequency) and how innovative, risky, and proactive those events are (degree).³

In total, we asked eleven questions. For each, we asked the respondent what their answer was today and what their response would have been three years ago. We sought to test three key hypotheses:

H1: (Successful) companies are shifting more toward an organization that resembles an ecosystem
H2: Companies who more resemble ecosystems outperform their peers
H3: Certain elements (to be determined) of an ecosystem brand most drive superior performance

In Appendix A: Quantitative Survey, you will see the specific questions we asked.

This summary serves to help more clearly and succinctly describe these questions and how they relate to each other.

Input Questions

Does your firm treat its people like intrapreneurs rather than employees?
Does delivering value to your end customer involve working with ecosystem partners?
Do you primarily work in decentralized units?
Are teams empowered to work with autonomy?
Are you better at spotting industry trends?
Is it easy to get resources (time and/or money) to pursue a new opportunity?
If you are not happy with the support you are getting from functions (e.g., IT, R&D), do you have alternatives to choose from?

Output Questions

Do your people take entrepreneurial actions more frequently?
Is that entrepreneurial action of a higher degree (innovative, risk-taking, proactive)?
[By multiplying the results of the two output we were able to calculate EI]

Results Questions

Are you now more successful at recruiting and retaining top talent?
Have you outperformed on financial metrics over the last three years?

The findings of this survey proved surprising in several ways. First, we found limited evidence to support our first hypothesis, that successful companies are shifting more toward an organization that resembles an ecosystem. Most respondents, when comparing their answers today versus three years ago, did indicate their firms were becoming less centralized, these results proved not to be statistically significant. Companies are evolving, but not so quickly as to be able to see a significant change over a three-year period.

However, we found very clear and statistically significant evidence to support our second hypothesis, that companies who more resemble ecosystems outperform their peers.

Finally, with regard to our third hypothesis—that certain elements of an ecosystem brand most drive superior performance—we did find several key input drivers that showed strong correlations with outputs and performance. These will be detailed in the next section of this White Paper.

See Appendix B: Quantitative Findings for a complete report of the findings.

Characteristics of the Post-Bureaucratic Organization

Our quantitative survey showed clear correlations with five organizational principles and higher levels of entrepreneurship. It even showed strong correlations between most of these and the less directly-related performance measures of the ability to recruit and retain top talent and financial performance.

This chart summarizes our findings:

Relative impact of each input measure to output and performance measures*

	Output and Performance
Inputs	Intensity	Recr/ retain	Financial
Intrapreneurs: treat employees as intrapreneurs	2.77	1.63	1.43
Multiple partner collaboration: deliver value through ecosystem partners	1.93	1.51	1.38
Decentralized units: operate as smaller decentralized teams	1.49	1.22	1.28
Autonomy: provide autonomy to teams	2.17	1.48	1.25
Spotting trends: pursue: adopt organizational principles that help employees spot emerging trends	4.02	3.31	2.32
Access to resources: it is easy to get time and financial resources to pursue new opportunities	1.89	2.16	1.82
Alternative teams: if not happy with shared services, units have alternative options	2.10	1.64	1.28

*The average score of a firm that scores 4 or 5 on an input measure divided by the average score a firm that scores a 1-3. For example, for “Intrapreneurs”, a firm that scores a 4 or 5 on intrapreneurship has an average entrepreneurial intensity score 2.77 times higher than that of a firm that scores a 1, 2, or 3 on intrapreneurship.

Source: Outthinker analysis

The Impact of Treating Employees Like Intrapreneurs

Relating to employees and intrapreneurs rather than entrepreneurs: firms who did this enjoyed a level of entrepreneurial intensity that was nearly 3X (277%) higher than their peers. They also are more likely to outperform their competition (143% more likely) and are better at recruiting and retaining top talent (163%).

As can be seen from the data below, companies whose employees feel they are related to as intrapreneurs, significantly outperform their peers in terms of entrepreneurial intensity, top talent recruitment and retention, and financial performance.

To clarify the format of the following set of charts, note that the figures to left of each matrix (1, 2, 3, 4, and 5) represent the score that an individual respondent gave to the question related to the specific input question. So, in this case, the question was, “To what extent do you agree or disagree with the following statement: Our organization treats its people more like intrapreneurs than employees?” to which they could have chosen 5 to mean “strongly agree” and 1 to mean “strongly disagree.” The figures at the top of each matrix represent the scores respondents gave to questions related to output and performance measures. In this case, you will note that of the respondents who strongly agreed that their company treated employees like intrapreneurs (who therefore scored their company a “5”), 44 of them also gave scores that resulted in an Entrepreneurial Intensity (EI) score of 21-25 while only one scored their company such that it resulted in a relatively low EI of 0-5.

Intensity

	0~5	6~10	11~15	16~20	21~25
5	1	12	9	28	44
4	4	14	24	61	9
3	17	41	20	23	6
2	18	18	10	15	1
1	22	17	6	8	3

Retention

	1	2	3	4	5
5	2	6	21	26	35
4	1	14	35	39	19
3	7	17	34	30	8
2	3	18	17	17	4
1	12	9	12	8	8

Financial Performance

	1	2	3	4	5
5	1	8	19	23	40
4	2	12	28	42	24
3	6	7	41	30	10
2	3	8	14	27	6
1	11	8	11	10	7

What is evident is a nearly linear correlation between Intrapreneurship input scores and output scores: if you score a 5 on intrapreneurship (i.e., if your people would strongly agree that they are treated as intrapreneurs rather than employees) you are most likely to also get the top score on intensity, retention, and financial performance. If you score 4 on intrapreneurship, you are mostly likely to get a 4 on intensity, retention, and financial performance.

The correlation breaks down at lower scores of intensity, so when your employees strongly disagree that they are treated as intrapreneurs, your intensity, retention, and financial performance can vary widely. This seems a logical pattern to us as when intrapreneurship is not a factor, then other factors will drive intensity, retention, and financial performance.

1

The Impact of Delivering Value Through Ecosystems

Companies that primarily deliver value to end-users through an ecosystem of partners are twice as likely (193%) to have high EI, are 1.5X (151%) more successful at attracting and retaining top talent, and enjoy more marginal, but significant superior financial performance (they are 1.4X or 143% more likely to outperform their peers).

Intensity

5	23	30	33	57	49
4	16	34	21	52	8
3	15	25	12	15	2
2	4	9	3	6	3
1	6	6	0	2	1

Retention

5	11	26	47	55	45
4	7	22	32	42	17
3	5	7	26	16	8
2	3	5	10	4	3
1	2	4	4	1	3

Financial Performance

5	13	16	44	55	54
4	5	10	36	49	20
3	2	9	25	18	7
2	2	9	3	9	2
1	2	1	3	1	5

2

The Impact of Operating in Smaller Decentralized Teams

While we expected that companies that organize themselves in smaller, decentralized rather than larger business units to enjoy a more significant advantage, the impact of such an organizational structure proved still statistically significant. Firms that adopt such an organizational model unleash greater entrepreneurial behavior (149%), achieve better financial performance relative to peers (128%), and are better at recruiting and retaining top talent (122%).

As with prior input measures, we see a strong correlation, especially at the higher levels. An input score of 5 means you will most likely score a five on intensity, retention, and financial performance. If you score a 4, you most likely will achieve a score of 4 on all four. Obviously other factors are at play (note that even with a score of 5, your intensity and retention scores may nearly equally be a 4s or 5s), but organizing as decentralized teams is a meaningful driver of success.

Intensity

5	7	19	21	34	35
4	14	32	18	49	10
3	14	26	16	23	3
2	14	19	7	19	3
1	16	9	7	11	13

Retention

5	7	13	27	32	35
4	11	19	34	41	11
3	4	11	34	21	5
2	3	14	14	13	12
1	6	7	11	12	14

Financial Performance

5	11	9	17	30	45
4	8	13	31	46	16
3	2	7	35	25	7
2	1	11	17	16	10
1	2	5	14	16	11

3

4

The Impact of Empowering Units and Teams to Act Autonomously

Empowering units and teams to act with autonomy and make their own decisions proved to be a powerful driver of EI. Firms that do this enjoy over 2X (217%) higher entrepreneurial rates (EI). They are also 1.5X (148%) better at recruiting and retaining top talent, and enjoy a more marginal, but significant advantage in financial performance (125%).

The question we asked here was, “To what extent do you agree or disagree with the following statement: Teams or units in the organization are empowered to act with autonomy and make their own decisions.”

Intensity

5	7	14	15	35	40
4	22	54	30	77	17
3	10	20	14	12	2
2	17	12	8	13	1
1	12	4	2	1	4

Retention

5	2	9	28	33	36
4	17	30	54	58	29
3	3	8	24	14	3
2	5	14	12	10	7
1	4	4	2	7	1

Financial Performance

5	2	10	23	36	35
4	9	23	53	61	36
3	4	6	19	14	7
2	4	6	16	17	6
1	4	1	3	6	5

5

The Impact of Introducing Models that Facilitate Employees Spotting Trends

Companies that introduce organizational models that facilitate employees spotting emerging customer and market trends enjoy a remarkable advantage over those who do not. This factor was the most significant of all the input measures we tested. Their EI is 4X (402%) higher, they are over 3X (331%) better at attracting and retaining top talent and are more than 2X (230%) more likely to outperform their peers financially.
This factor, we feel, deserves deeper analysis, specifically to understand what organizational tools in the RenDanHeYi or other decentralized models enable an organization to be better at spotting trends.

Intensity

5	10	11	18	39	56
4	9	33	29	76	6
3	23	45	17	18	1
2	9	13	4	3	0
1	11	4	1	1	0

Retention

5	2	11	22	43	49
4	4	23	43	60	18
3	5	24	47	11	6
2	9	6	5	5	0
1	10	1	2	2	1

Financial Performance

5	2	4	19	35	66
4	4	15	45	68	15
3	5	15	40	23	6
2	6	9	5	6	1
1	7	2	4	2	0

6

The Impact of Making It Easy to Get Resources to Pursue New Opportunities

Solutions that facilitate employees accessing resources, time, and support to pursue new ideas is a powerful driver. Companies who make this easy for employees are about twice as likely to have high levels of entrepreneurship (189%), enjoy an advantage at recruiting and retaining top talent (216%), and to outperform their peers (182%).

While traditional hierarchical organizations have implemented approaches to facilitating this (such as idea competitions, dedicated innovation funding, carving out innovation teams to provide support), our interviews of internal innovators indicate that these approaches are viewed by employees most often as ad-hoc and unsustainable. Instead, more decentralized models like RenDanHeYi adopt a philosophy that allows employees to act without formal authority. This is consistent with research that shows a strong correlation between organizational structures and cultural norms that encourage autonomous action.⁴

Intensity

5	9	8	15	17	38
4	10	33	24	63	20
3	18	34	13	26	2
2	13	22	13	23	1
1	17	8	4	8	3

Retention

5	1	4	13	29	34
4	5	22	38	56	23
3	7	11	41	17	10
2	4	21	22	15	4
1	14	7	6	3	6

Financial Performance

5	1	4	12	24	37
4	2	18	31	61	29
3	4	10	39	20	12
2	6	11	23	21	6
1	11	3	9	7	5

7

The Impact of Letting Employees Choose from Support Functions

Giving units or team who are not satisfied with the support they are getting from a function like IT, finance, or legal, other options. While fewer companies adopt such practices than the other practices tested, those who do enjoy far higher levels of EI (210%), recruitment and retention (164%), and more marginal but significant advantage in financial performance (128%).

This organizational principle is, in our view, one of the most exciting and radical of the RenDanHeYi characteristics studied. Whenever we have shared this idea within large, established organizations, we have found great resonance with the idea. Adopting such flexibility implies a potentially radical reconfiguration of the firm.

Intensity

5	3	3	10	23	26
4	5	12	12	39	14
3	5	32	20	25	8
2	11	23	13	25	2
1	41	33	11	20	13

Retention

5	0	4	11	22	28
4	4	9	25	30	13
3	1	10	31	24	16
2	7	19	24	13	8
1	17	21	27	28	11

Financial Performance

5	0	4	16	16	27
4	3	9	20	36	13
3	0	9	35	22	16
2	5	10	15	27	13
1	16	14	23	29	19

A Note on Statistical Significance

The seven organizational principles proposed earlier were correlated individually with each output. A simple two-tailed T-test at a significance level of 5% (α =.05) was used to detect any significant results. The tables X & Y & Z below summarize the correlation coefficients and the statistical significance of the p-values.

r = correlation coefficients

		Frequency	Degree	Overall Intensity	Financial Performance	Attract and retain talent
Intrapreneurs	Today	0.49	0.50	0.54	0.35	0.34
Intrapreneurs	3 Years ago	0.47	0.49	0.51	0.32	0.31
Multiple Partner Collaborations	Today	0.28	0.26	0.28	0.24	0.21
Multiple Partner Collaborations	3 Years ago	0.28	0.26	0.27	0.26	0.20
Decentralized Units	Today	0.29	0.26	0.26	0.20	0.17
Decentralized Units	3 Years ago	0.26	0.26	0.26	0.22	0.18
Act with Autonomy	Today	0.41	0.40	0.41	0.21	0.30
Act with Autonomy	3 Years ago	0.43	0.42	0.42	0.24	0.28
Spotting trends	Today	0.55	0.54	0.56	0.47	0.42
Spotting trends	3 Years ago	0.51	0.53	0.53	0.42	0.38
Ease of resources	Today	0.40	0.35	0.41	0.30	0.37
Ease of resources	3 Years ago	0.39	0.37	0.39	0.28	0.31
Alternative choices	Today	0.43	0.39	0.43	0.30	0.39
Alternative choices	3 Years ago	0.40	0.37	0.39	0.28	0.34

Table X

p-value

		Frequency	Degree	Overall Intensity	Financial Performance	Attract and retain talent
Intrapreneurs	Today	1.00574E-28	1.40162E-29	9.21356E-35	2.10653E-14	1.56833E-13
Intrapreneurs	3 Years ago	1.73087E-26	5.70842E-28	4.54173E-31	6.99388E-12	1.85602E-11
Multiple Partner Collaborations	Today	8.13273E-10	2.05084E-08	2.59382E-09	3.63202E-07	5.5879E-06
Multiple Partner Collaborations	3 Years ago	1.15036E-09	1.25725E-08	5.1619E-09	2.58437E-08	1.62409E-05
Decentralized Units	Today	7.64071E-10	1.25043E-08	1.80955E-08	1.51652E-05	0.000195283
Decentralized Units	3 Years ago	2.31398E-08	1.60767E-08	3.0972E-08	4.08502E-06	0.000156639
Act with Autonomy	Today	1.10948E-19	7.1615E-19	1.17486E-19	6.2503E-06	1.06335E-10
Act with Autonomy	3 Years ago	1.2755E-21	2.57681E-20	1.11489E-20	2.33789E-07	1.03974E-09
Spotting trends	Today	1.4277E-37	4.85296E-35	3.88981E-38	1.20997E-26	6.49513E-21
Spotting trends	3 Years ago	1.28367E-30	1.41018E-33	2.35959E-34	9.89545E-21	1.05389E-16
Ease of resources	Today	1.63021E-18	1.9069E-14	1.2066E-19	6.42616E-11	7.9354E-16
Ease of resources	3 Years ago	7.4182E-18	4.89912E-16	5.98375E-18	1.07018E-09	8.73659E-12
Alternative choices	Today	3.5922E-21	1.55926E-17	2.89218E-21	1.21258E-10	1.93307E-17
Alternative choices	3 Years ago	1.01938E-18	9.68688E-16	4.71175E-18	1.87161E-09	1.13443E-13

Table Y

Significance

		Frequency	Degree	Overall Intensity	Financial Performance	Attract and retain talent
Intrapreneurs	Today	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Intrapreneurs	3 Years ago	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Multiple Partner Collaborations	Today	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Multiple Partner Collaborations	3 Years ago	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Decentralized Units	Today	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Decentralized Units	3 Years ago	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Act with Autonomy	Today	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Act with Autonomy	3 Years ago	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Spotting trends	Today	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Spotting trends	3 Years ago	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Ease of resources	Today	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Ease of resources	3 Years ago	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Alternative choices	Today	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant
Alternative choices	3 Years ago	Statistically significant	Statistically significant	Statistically significant	Statistically significant	Statistically significant

Table Z

As we can see in Table Z, our results show that all seven principles are significantly correlated with the output and performance variables.

These seven organizational principles suggest we may be headed not toward an evolution of the traditional bureaucratic model but, we believe, a departure from it. Our belief is based on three reasons:

They show measurable advantages over traditional organizational approaches both in terms of firm financial performance and a firm’s ability to attract and retain talent (so both on the customer side and the employee side).
They are inconsistent with, or at least unnatural to, traditional bureaucratic models so they force companies to either isolate them (in an ambidextrous org) or choose to abandon traditional models.
They are choices that firms can take action on now. Indeed, forward-looking companies already are taking such action.

In the case of Adobe, employees are invited to attend a training and then given a box which contains everything an employee needs to test a new innovation idea. As described in a 2015 Harvard Business Review article on the Adobe Kickbox methodology: “The top of the box features a clever fire alarm image with the words ‘Pull in Case of Idea’ written on it.

When you break open the seal, you’ll find instruction cards, a pen, two Post-It note pads, two notebooks, a Starbucks gift card, a bar of chocolate and (mostly importantly) a $1,000 prepaid credit card. The card can be used on anything the employee would like or need without ever having to justify it or fill out an expense report.”⁶

MIT professor Michael Schrage, who we interviewed for this research, popularized a program that traditional hierarchical organizations can introduce to activate entrepreneurial intensity by making it easier for employees to get the resources and time needed to take action on new ideas. He calls it the “5 X 5 Experiment,” which advocates for pulling together a diverse team of five employees to come up with five experiments, each of which can be tested within five weeks, for under $5,000 each.⁷

There is no shortage of programs and frameworks and hacks that traditional organizations apply to compensate for some of the restraints a centralized model imposes on agility and entrepreneurialism. In other words, there are numerous attempts at work to incorporate some of the seven organizational principles described here into the existing bureaucratic paradigm.

But we believe ultimately, the organizational structure taking form cannot co-exist with a traditional bureaucracy. We believe this for two reasons:

1

It may not seem a big stretch to evolve a bureaucracy so that it can adopt one or two of the seven principles described above, but adapting all seven becomes an effort big enough to cause one to consider simply redesigning the organization from scratch. This is akin to refurbishing a house. Installing some windows or chandeliers is easy enough. But when you decide to also replace the plumbing, move walls, and lay the foundation for a new extension, it becomes more economical to simply demolish the house and build anew.

2

Several of the seven contours are actually inconsistent with bureaucracy. At the very least they are inconvenient for a bureaucracy to assume. In some cases, their adoption would mean abandoning a characteristic that defines what a bureaucracy is. In such a case, adopting a characteristic would mean, by definition, to cease being a bureaucracy.

To see point 2, that adopting some elements of the emerging organizational model means to cease being a bureaucracy, consider Max Weber, the German political economist who in the early 1920s, popularized bureaucracy as the most efficient approach with which to organize human activity (though he did also warn that, left unchecked, bureaucracy can reduce individual freedom). He is arguably the most influential authority on the topic of bureaucracy. In defining bureaucracy, he wrote that an effective bureaucracy must include several things, including:

a hierarchy,
with clear lines of authority,
that divides labor into specialties,
with the quality of decisions being strictly regulated.

These seven principles described above imply organizational structures that look more like autonomous ecological systems, or marketplaces or ecosystems, of autonomous teams rather than hierarchies. They suggest erasing clear lines of authority, instead leaving the establishment of authority up to the system. For example, in Haier’s RenDanHeYi model, the CEO of a Microenterprise (ME) can be voted out if their team does not feel they are doing a good job. An IT department (also an ME) loses funding if it cannot secure internal clients, not because a budgeting authority removes funding, but because internal marketplace of MEs do not value the IT department’s offer. Instead of dividing labor into specialties, specialists are mixed with non-specialists (or other types of specialists) in a small team. And the quality of decisions is not regulated, at least not by a central authority, but rather by supply and demand dynamics of the internal marketplace. In other words, adopting all seven of these characteristics in an organization would mean to abandon hierarchy, erase clear lines of authority, mix specialized labor rather than dividing it, and letting the internal marketplace judge the quality of decisions rather than regulating them. Such an organization cannot, by Weber’s definition, be considered a bureaucracy.

Why Now

We have argued here that we are reaching an inflection point at which frustration with traditional centralized models is culminating, finally, into clarity on a potential solution. But why should it be that we are reaching this inflection point now? Why did we not start settling on an alternative bureaucracy ten years ago? The answer is technology. Specifically, a bundle of technologies and practices are reaching a level of maturity that collectively enables us to organize in forms that heretofore were not possible, or at least forms that until now were not as efficient or effective as bureaucracy.

To see this, it’s important to remember when and why centralized organizational structures exist. In 1937, British economist Ronald Coase published a highly influential article titled “The Nature of the Firm” (1937), which argued that to understand when firms (companies) emerge and to understand their limitations, we should look at transaction costs. Simplifying his theses here, consider that transactions can be executed either internally, within the rules and structure of a firm, or externally through a marketplace. A transaction might be purchasing raw material or supplies, hiring talent, selling through another party, etc. Whenever it is less expensive to execute the transaction internally, then a firm will be more competitive than a marketplace.

The cost of a transaction includes things like the cost to search (e.g., for a supplier), negotiate, protect trade secrets, police or enforce the trade, all of which can add to the full transaction cost. For example, if every day you had to find a specialized worker to operate a piece of machinery in your factory, you may find it more economical to hire that person as an employee (thereby becoming a firm) than to search for a new expert, negotiate a fee, sign a contract, and ensure you protect trade secrets that person may learn every day.

Firms compete with marketplaces. Wherever they can clear a transaction more economically than the marketplace, the firm takes over. Whenever the marketplace is more efficient, the market takes over.

A number of technologies, however, are reducing the costs of completing transactions outside of hierarchies, making non-hierarchical alternative more competitive alternatives to the firm. Many of these technologies are often bundled together as “4th Industrial Revolution” (4IR) technologies. Swiss Economist, Mark Esposito, wrote “The 4IR is a combination of emerging technologies that is shaping the way we live and work. The Internet of Things (IoT), cloud computing, big data, robotics, artificial intelligence (AI), 3D printing, augmented reality (AR), virtual reality (VR), nanotechnology, and biotechnology are the technologies that are gaining more prominence during the twenty-first century and are overlapping and fusing with one another in this age of innovation.”⁸

These technologies, in combination, allow us to coordinate people, companies, and activities with greater accuracy and speed than before. We have already seen the impact of these technologies advancing the rise of “gig workers” through platforms like Task Rabbit, Upwork, or Uber. These technologies reduce search costs (you can find a gig worker in minutes with a few clicks rather than through hours of phone calls), negotiation costs (instead of negotiating fees and terms, the platform sets them for you), and enforcing acceptable performance (allowing you to digitally rate the worker and the worker to rate you the platform can create accountability more quickly and at a lower cost than, say, managing regular performance reviews with an internal hire).

And the technology that has enabled gig-working platforms is far more rudimentary than what is now possible. Chairman Zhang Ruimin of Haier, indeed, calls this era the “IoT Era” in which machines communicate with humans and other machines, data proliferates, which then feeds AI algorithms, protected by blockchain networks, all of which are driving down transaction costs rapidly below what centralized hierarchies can deliver.

A bureaucracy can be competitive if it can deliver a lower transaction cost. That cost is composed of six elements:

1

Search costs

2

Assessment costs

3

Negotiation costs

4

Delivery coordination costs

5

Compliance costs

6

Trade secret protection costs

If a hierarchy can give you the best option to search, assess, negotiate, coordinate delivery, ensure compliance, and protect any trade secrets better than a decentralized alternative, the hierarchy will and should own the transaction. The issue is that, while bureaucracies are losing ground to marketplaces that, thanks to these technologies, are becoming more competitive and to new forms of organization, examples of which we will discuss later.

If a hierarchical firm is to hold on to its current reach, it will need to adapt how it coordinates in order to reduce transactions costs. Otherwise, it will not remain competitive and will eventually lose to alternatives.

Organizations are adapting, but a step behind technology. There is always a lag between what technology makes possible and the adoption of that technology by users of that technology. The same is true here in the application of these technologies.

As these technologies reduce transaction costs outside of firms, they are forcing firms to either cease activities they once conducted in-house or adopt more decentralized coordination models that are able to deliver transactions more competitively. Such models more closely mirror that of external marketplaces and other decentralized models. If they do not, as Martin Reeves said in a recent interview we conducted for this research, “the firm will retract to become the coordinator of coordination.”

More broadly, these technologies are thrusting upon us several new realities to contend with, for example:

They allow us to create both efficient and highly-personalized experiences as University of Michigan professor, Venkat Ramaswamy, suggested in an interview we conducted with him regarding this research
They generally accelerate the pace of change
They shift us from transactions to relationships, from products to experiences, from customers to experiencers
They move us away from one firm providing the product toward an ecosystem of coordinated but independent firms creating the experience (i.e., because coordinating independent firms becomes easier)
They are likely to make data universally available, timely, and democratized

Bureaucracy Faces New Competitors

Coase’s work pitted firms against marketplaces. But today’s firm must compete not just with marketplaces (or even platforms), but with a new generation of organizational forms that were impossible to create or even imagine five years ago.

We see the proliferation of new decentralized models across a range of industries. Crypto currencies are offering viable alternatives to fiat currency. Decentralized finance is shaping the banking sector. Companies like Holtzbrink, the world’s largest publisher of scientific journals, is exploring decentralized science in which rights to scientific advances are not controlled or owned by publishers or universities, but by the scientists who created them.

Decentralized Autonomous Organizations (DAOs) are also forming across a range of sectors. Such organizations are built on blockchain and other Web3 technologies.

This new form of legal structure has no central governing body. Instead, every member of a DAO shares a common goal and acts in the interest of the DAO. Decisions are often made and enforced through a set of rules, implemented by “smart contracts”—programs that act like contracts, but that don’t need a human executor to dictate actions, rather, the program trigger actions automatically. The DAO model encourages emergence of coordinated effort from the bottom up rather than imposing it from the top down. You might think of a DAO as technology-enable co-op.

Consider, for example, dOrg⁹, one of the very first DAOs to be legally recognized as an LLC in the United States. Formed in 2019, dOrg is a decentralized software company dedicated to helping build infrastructure for Web 3 and crypto projects.

There are no formal roles – no CEO or CFO or head of HR. Each member/worker is an owner of the legal corporation, a Vermont-based LLC. Company decisions are voted on using tokens, which members earn for completing projects for the company. The more projects you complete, the more tokens you own, and the more votes you can cast.

Or consider Seed Club¹⁰, a DAO that “builds and invests in communities” and does so because “We’re building a future where the value created by communities on the internet is captured by people, not platforms.” Members of this DAO are paid in two different cryptocurrencies. One they can convert into fiat currency to pay for things like food and rent. The other is a coin that gives them ownership in the DAO.¹¹

The evolution of DAOs today is far too early to know if this form of organization will succeed. But they offer one other example of an alternative organization form made possible by advances in IoT, blockchain, AI, and other 4IR technologies.

Such models might not even qualify as “organizations” in the common understanding of the term. They can coordinate effort for short-term projects. They can enable people and machines to swarm around new opportunities or threats, then disband, then reconfigure with new sets of members to address a different challenge, opportunity, or project.

The bureaucracy is not only competing with Coase’s marketplace. It is competing with a diverse and evolving set of new organizational forms. Given this, why should we not expect similar models to start taking over how firms organize? If the firm is to remain relevant, it must evolve to realize the transaction advantages available by new technology.

References

See www.outthinkernetwork.com

Donald Sull, Rebecca Homkes, and Charles Sull, last modified March 1, 2015, "Why Strategy Execution Unravels—and What to Do About It," Harward Business Review, https://hbr.org/2015/03/why-strategy-execution-unravelsand-what-to-do-about-it

Morris, Michael. (2015). Entrepreneurial Intensity. 10.1002/9781118785317.weom030029.

See Kaihan Krippendorff, Driving Innovation from Within

See https://www.kickbox.org/

See https://hbr.org/2015/02/inside-adobes-innovation-kit#:~:text=The%20Kickbox%20is%20a%20small,and%20measurably%20improve%20innovation%20outcomes.%E2%80%9D, access September 12, 2022.

https://news.mit.edu/2014/michael-schrage-book-business-experiments-innovation-1007

Esposito, Mark and Kapoor, Amit, The Emerging Economies under the Dome of the Fourth Industrial Revolution, Cambridge: Cambridge University Press, July 2022

See https://www.dorg.tech/#/

See https://www.seedclub.xyz/

See https://www.wbur.org/news/2021/10/28/decentralized-work-dao-blockchain