Category: Innovation

Assessing Innovation Capability

The full-blown industry of innovation management consulting includes the usual complement of academia; professional services including training; the business media; and experienced in-house FTEs. At the same time, measures of success more often seem to exist only within the small percentage of organizations that already perform innovation well, somewhat like trade secrets. And from the outside, once we exclude the top ten lists, it is difficult to distinguish between exceptional success and repetitive success among all others. Finally, much more is heard about the difficulty of being successful than about the confidence of becoming successful. Since innovation is now a default imperative in most businesses getting press, this situation is not one that will remain unchanged.

Changing it leads to the need for identifying the key factors and indicators involved in successes and failures, and being able to compare them.  But an interesting and persistent problem is that so far, despite years of effort, both practitioners and motivated researchers offer such a wide range of differences in descriptions, explanations, methods and priorities for addressing the capability to innovate. This might simply reflect the true level of complexity of innovating successfully, but what we don’t know is whether the apparent complexity is originating in certainty or in uncertainty.

The challenge of reaching consistency in matching different ideas and approaches to successful outcomes also reflects two familiar problems. One is the problem of not being aware of what is unknown yet needs to be known. The other is the difference between correlation and causation. In both cases, guidance is needed for deciding what to look for and what to notice about it. And per the subsequent discovery, is innovation more like chess, or more like physics?

In the following discussion, an Archestra framework has derived from first surveying how people talk about innovation, with a special emphasis on what distinctive but general topics have most often recurred as “highly important” across the breadth of roles and environments cited. The initial perspective is very high level:

Innovation as Generic Production Capability

The further exploration is essentially about the underlying semantics that cross circumstantial boundaries of the speaker’s roles and environments. We classified the recurring discussion subjects and topics into two groups of meaning: one about the general subject of opportunity to innovate; and the other about the general subject of actually generating the innovation. We also took each group’s individual topics as placeholders to each be interpreted into corresponding issues about intent and about execution.

Opportunity topics and their related terms:

Innovation Opportunity Topics

Actualization topics and their related terms:

Innovation Actualization Topics

The final interpretive work cross-references the opportunity versus actualization issues for intent, and the opportunity versus actualization issues for execution, yielding two corresponding frameworks for the “front end” of innovation capability and the “back end” of innovation capability, respectively. These frameworks call out the specific factors contributing to the capability to innovate. See the documentAn Innovation Capability Assessment Framework for the detailed discussion of the frameworks.

The Design of Services

We intuitively understand that services allow us to have or do things that we don’t make or perform for ourselves. In theory, the best case scenario is that available services are tightly aligned to both our desires and our expectations. That brings in a variety of stakeholders who can create, use, and assure things heading in the right direction. But expressing what is needed, and how, to achieve the best scenario is often too imprecise and confusing to adequately work out, complete, and sustain or remodel against current and future circumstances.

The Archestra framework of service design parameters is an evolving artifact. Shown here is the framework as of May 2015.

The framework is an instrument for consistently identifying variable factors by which a service is obtainable and evident across its varying states of relevance (what service is the “right” one) and worth (what is the “upside” of the service). A single service may be “identified” through a variety of descriptive points of view; the framework contains them within a logical system of cross-references. Note (again) that the whole framework is used to refer to any single given service.

Service Design Parameters 2015

Goals of the framework:

  • Simple, explicit overall perspective
  • Uniformly global and pragmatic
  • Equally synthetic and diagnostic
  • Based on observable practices and events


  • No logical redundancies or contradictions
  • No reliance on a specific industry, business, process or technology vocabulary
  • No need for synonyms


  • Completely neutral: devoid of marketing, sales and philosophy clutter
  • Entirely compatible with governance, risk and asset management
  • Agnostic to physical vs. virtual, and actual versus logical, service formats
  • The semantics work the same way across Blueprints, Inventories, CMDBs, Portfolios and Catalogs, which intentionally select and assert distinctive views


  • Recognizes any manageable variable that can change the service structure or service status
  • Assures that any instantiated variables (realized actuals) are fully contextualized
  • Assures that different variables are never mistaken for each other


  • Supports classic modeling by exposing the identification, selection, integration and coordination of instantiated variables.
  • Shows that construction and deconstruction follow the same pathway
  • Shows that absence-or-presence of service is a logical threshold in a defined context, thus enabling knowledge-driven systematic problem management, policy determination, and renovation/innovation


Performing Innovation Under Governance

For those who manage performance, governance appears to offer a layer of security for meeting performance targets. But the scope of governance’s concern naturally exceeds the scope of production performance, representing a need to protect opportunity above and beyond performance targets. Inappropriate performance management will hold back innovation unless governance is appropriately influential on production.



The notebook accompanying this table traces the influence on the production environment that governance brings, with regards to supporting innovation. Click here to access the notebook.


The Tao of “New”

“New” changes. Newness doesn’t.

Back in April of 2007, Optimize Magazine ran an article by M.S. Krishnan titled Moving Beyond Alignment. Its summary: strategic business innovation requires a flexible infrastructure so that the company can utilize the business models needed to achieve goals. Thus IT governance and architecture must enable the enterprise to “synchronize with changes in the business environment”.

Meanwhile, scheduled for late 2010, the book from strategic technology architects Greg Suddreth and Whynde Melaragno called The Path to Real Business Transformation discusses “dynamic synchronization… a rigorous, business-case-driven collaboration between the business-process owners and their IT counterparts.” For this, the framework of problem-solving is what they call business architecture.

“Innovation” always has an aura that suggests the big moment of arrival of the new. But getting to utilize the new is the only way that value is derived from innovation, and utilization requires integration into, and synchronization of,  the operational scheme of things. This emphasis on synchronization firmly declares that the problem of follow-through on business strategy is fundamentally about coordinating the moving parts.

Anyone who has tried to manually shift gears in a moving vehicle knows that synchronization has two operator-controlled aspects: time spent in the gear, and timing of gear changes. In a competitive context, where time and timing are pre-planned and managed for variances and circumstantial adjustments, this plan is even seen as a strategy itself. The performance level of the plan’s execution, especially in complex or volatile environments, is then most often seen as “agility”. Achieving agility is, for that reason, a common business objective related to scoring business goals.

Suddreth and Melaragno further state that “business architecture” is developed through a process that defines and institutes long-term change within a framework of strategy (for example of goals, related positions and directions), planning (for example, of resources), and execution (for example, of services). They go on to point out that multiple business areas must be complementary in the context of solving a defined business problem.

To assure proper pursuit of that agreement, it becomes necessary to appreciate the difference between innovative business uses of IT versus business use of innovative IT.

  • In the former case, the emphasis is on the business-level understanding of how moving parts might be aligned in a new way.
  • In the latter, the point is to introduce moving parts that have a different set of characteristics and interactions than those typically tried before.

From the point of view of these authors, the former issue is a concern of business architecture; and the latter issue is a concern of IT architecture, in which (among other things) the business architecture is  “physicalized” according to Suddreth and Melaragno.

Given those points above, it would seem that the challenge is to prioritize business innovation, then leverage business architecture to identify and incorporate IT innovation that can be scheduled within IT architecture for a reasonable chance of sustained synchronization.


The Evolution of Insight, in Hindsight

The most amazing part of the legacy of IT innovation in 2007 to 2015 is the number of different ways that individuals had to initiate action. The vast expansion of options had an unprecedented reliance on underlying support mechanisms that were heterogeneous, spontaneous, or ungoverned in their availability and presence.

In particular, conventional controls on interaction such as policies (permission) or configurations (structures) faced conditions so diverse or even ephemeral that achieving operational predictability was possible only on fundamentally new terms.

Today and going forward, the new normal environment of operations for users is even more heterogeneous and “open”. Managing production in that environment requires insight into what the environment already wants to support and do systemically, which can then be exploited under management.

The driving metaphors for that environment’s state of affairs are “organic” and “Darwinian”. Native elements coincide, combine, and compete.

As an overall ecosystem, the complex set of relations in this new state pose a big challenge to discovering the regularity of its dynamics — the probabilities showing  a “natural” set of priorities, and the most common attributes of “natural” constructions. Without that information, imposing practical preferences and mitigating risks is far more difficult.

This throws us into a scientific mode of achieving a practical familiarity. The ability to “look into the system” and recognize its behavior is the insight that matters.

In general, we first maintain continuous observations from which events, transactions and outcomes are revealed.

Then we aggressively analyze those observations, to identify any significantly persistent correlations.

Finally, the most useful logical modeling of those correlations will characterize and reveal co-operative agents and brokers in the system.

The Evolution of Insight


Creativity Under the Microscope

When we go to the underlying “template” of nearly all discussions about “creativity”, our main interests, are always the same:

– How do you recognize it?
– Where does it come from?
– How do you use it?
– Who cares?
– What is it worth?

We know what the word “create” means: it means “to make”. Competitively, we want creativity to refer to making things in a way that they were not made before — a strategically useful requirement. We want to know if those new “formulas” are inspired (implicitly discovered) or engineered (explicitly discovered), and we want to know if we can cause the discovery on demand.

But the terms of discussions about creativity are often too ambiguous to be shared effectively across different parties. The ambiguity inhibits both confidence and progress in taking creativity under management.

A glossary of characteristic distinctions would help to sort out the discussions so that the answers provided would be understood the same way by all of the participants.

Most of the mythology about creativity is actually about where it comes from — namely, the nature of “inspiration“. Creativity is seen most commonly as “originality of awareness”, usually characterized in one of two ways:

– insightful (sees within)
– imaginative (foresees)

But artists, teachers and coaches know that creativity can be both taught and learned as a behavior that generates insight and imagination. The behavior has any or all of the following characteristics:

– playful (arranging for pleasure)
– experimental (arranging for discovery)
– inventive (arranging for newness)

– constructive (static effectiveness)
– productive (dynamic effectiveness)

– distinctive (different per specification)
– unusual (different per context)
– original (different per known precedent)

Overall, the glossary allows us to “map” these behaviors as  different types of “vision” (seeing), “build” (arranging),  “impact” (effectiveness) and “value” (difference).

It’s fair to ask about how the behaviors become competencies.

The answer is that the behaviors can be pursued intentionally and need not be only spontaneous or “inherent”. In particular, we see training as the work done in any behavior to separate the 80% of unnecessary effort from the 20% of effort worth amplifying. The other key effort required is planning. By looking at what each different behavior is actually about, it can be taken and prioritized as a potential source of change to a current state reality.



De-Myth-ifying Business Creativity

Because it is now accepted that innovation is a competitive imperative, Business Creativity is a subject with strong legs. It gets to play in thinking about resources, competencies, strategies, and environments — nearly all of the Big Management games.

But the real topic of the “business” discussion about creativity is usually this: “How Do I get Great New Ideas When I Need Them?”

The myth of management is “Do what worked before, and it will work again.” In that light, the ways to get ideas fall into only a few categories:

(a.) Find them;

(b.) Steal them;

(c.) Make them.

A more specific catalog of  “How To” efforts (find, steal, make) is necessary, but insufficient. Someone will invariably point at something and ask the question, “How do I know that is going to work?”

In reality, the answer is, “Well, you don’t.” And the reason why is that creativity is inherently unpredictable.

Almost any competent artist can tell us that “creativity” consists of (a.) labor, (b.) imagination, and (c.) inspiration, even though those three things don’t always occur in the same order or at the same time or degree. So creativity is also about being overtly opportunistic about all three.

This clarifies thinking a lot. Things that get in the way of laboring, imagining, and getting inspired are pretty much a lock to inhibit creativity. 

Said differently, “creativity” is not an event. It’s a condition that is fostered by a culture. A culture of low inhibition is simply more likely to host creativity.

Sometimes, the “condition” is one person’s free-associating mentality in the shower; sometimes it is a large operational unit ‘s new perspective – a groupwide view, acquired from research or hearsay, of a near future that it might know how to make…

Summarizing: “Business Creativity” is not about causing creativity. Instead; managing “business” creativity is fundamentally about managing how the business’s own ideas of risk are applied to an un-inhibiting culture.


The Accidental versus the Intentional: Creativity as Discovery

In most of the global business writing today about innovation,  “Creativity”  gives “Agility” a neck-and-neck run for the money.

Almost no one tries to explain innovation without reference to creativity. But the definition of “creativity” — something everyone needs and wants —  is often left unexamined, even as people presume it can be managed for “innovation”.
Creativity is intentional discovery, as distinguished from accidental discovery. It can be recognized when it’s there, and it can be cultivated so as to become a practice “in effect”.
A quick glossary of Creativity from an Innovation point of view:
  • The value of creativity is discovery.
  • The effect of creativity is invention.
  • The operation of creativity is experimentation.
  • The subject of creativity is structure.
  • The skill of creativity is composition.
Given those terms, there are still certain limitations on what creativity provides to innovation.
  • an invention may be new to its maker without being new to the world. It is possible that the same thing can get invented at multiple places or times, completely independently of each other.
  • a discovery is not necessarily of a “new” thing. Things that have already been discovered may get independently discovered again through different means and/or by different parties, therefore also possibly at different places or times.
As a result, innovation is not based on the uniqueness of creativity. This may at first seem to make “management” more difficult, in terms of control. But the more important aspect is in terms of development —  noting that multiple wide ranging sources of creativity can be called upon to support a more singular innovative concept or outcome.