Systematic Innovation

John BoydInnovation is a journey, and it starts from where you are.  With a systematic approach, the right information systems are in place and are continuously observed, decision makers use the information to continually orient their thinking to make better and faster decisions, actions are well executed, and outcomes of those actions are fed back into the observation system for the next round of  orientation.  With this method, the organization continually learns as it executes – its thinking is continually informed by its environment and the results of its actions.

To put one of these innovation systems in place, the first step is to define the group that will make the decisions. Let’s call them the Decision Group, or DG for short. (By the way, this is the same group that regularly orients itself with the information steams.) And the theme of the decisions is how to deploy the organization’s resources.  The decision group (DG) should be diverse so it can see things from multiple perspectives.

The DG uses the company’s mission and growth objectives as their guiding principles to set growth goals for the innovation work, and those goals are clearly placed within the context of the company’s mission.

The first action is to orient the DG in the past.  Resources are allocated to analyze the product launches over the past ten years and determine the lines of ideality (themes of goodness, from the customers’ perspective).  These lines define the traditional ideality (traditional themes of goodness provided by your products) are then correlated with historical profitability by sales region to evaluate their importance. If new technology projects provide value along these traditional lines, the projects are continuous improvement projects and the objective is market share gain. If they provide extreme value along traditional lines, the projects are of the dis-continuous improvement flavor and their objective is to grow the market.  If the technology projects provide value along different lines and will be sold to a different customer base, the projects could be disruptive and could create new markets.

The next step is to put in place externally focused information streams which are used for continuous observation and continual orientation.  An example list includes: global and regional economic factors, mergers/acquisitions/partnerships, legal changes, regulatory changes, geopolitical issues, competitors’ stock price and quarterly updates, and their new products and patents.  It’s important to format the output for easy visualization and to make collection automatic.

Then, internally focused information streams are put in place that capture results from the actions of the project team and deliver them, as inputs, for observation and orientation.  Here’s an example list: experimental results (technology and market-centric), analytical results (technical and market), social media experiments, new concepts from ideation sessions (IBEs), invention disclosures, patent filings, acquisition results, product commercialization results and resulting profits.  These information streams indicate the level of progress of the technology projects and are used with the external information streams to ground the DG’s orientation in the achievements of the projects.

All this infrastructure, process, and analysis is put in place to help the DG make good (and fast) decisions about how to allocate resources. To make good decisions, the group continually observes the information streams and continually orients themselves in the reality of the environment and status of the projects.  At this high level, the group decides not how the project work is done, rather what projects are done.  Because all projects share the same resource pool, new and existing projects are evaluated against each other.  For ongoing work the DG’s choice is – stop, continue, or modify (more or less resources); and for new work it’s – start, wait, or never again talk about the project.

Once the resource decision is made and communicated to the project teams, the project teams (who have their own decision groups) are judged on how well the work is executed (defined by the observed results) and how quickly the work is done (defined by the time to deliver results to the observation center.)

This innovation system is different because it is a double learning loop.  The first one is easy to see – results of the actions (e.g., experimental results) are fed back into the observation center so the DG can learn.  The second loop is a bit more subtle and complex.  Because the group continuously re-orients itself, it always observes information from a different perspective and always sees things differently.  In that way, the same data, if observed at different times, would be analyzed and synthesized differently and the DG would make different decisions with the same data. That’s wild.

The pace of this double learning loop defines the pace of learning which governs the pace of innovation.   When new information from the streams (internal and external) arrive automatically and without delay (and in a format that can be internalized quickly), the DG doesn’t have to request information and wait for it. When the DG makes the resource-project decisions it’s always oriented within the context of latest information, and they don’t have to wait to analyze and synthesize with each other.  And when they’re all on the same page all the time, decisions don’t have to wait for consensus because it already has.  And when the group has authority to allocate resources and chooses among well-defined projects with clear linkage to company profitability, decisions and actions happen quickly.  All this leads to faster and better innovation.

There’s a hierarchical set of these double learning loops, and I’ve described only the one at the highest level.  Each project is a double learning loop with its own group of deciders, information streams, observation centers, orientation work and actions.  These lower level loops are guided by the mission of the company, goals of the innovation work, and the scope of their projects.  And below project loops are lower-level loops that handle more specific work.  The loops are fastest at the lowest levels and slowest at the highest, but they feed each other with information both up the hierarchy and down.

The beauty of this loop-based innovation system is its flexibility and adaptability.  The external environment is always changing and so are the projects and the people running them.  Innovation systems that employ tight command and control don’t work because they can’t keep up with the pace of change, both internally and externally.  This system of double loops provides guidance for the teams and sufficient latitude and discretion so they can get the work done in the best way.

The most powerful element, however, is the almost “living” quality of the system.  Over its life, through the work itself, the system learns and improves.  There’s an organic, survival of the fittest feel to the system, an evolutionary pulse, that would make even Darwin proud.

But, really, it’s Colonel  John Boyd who should be proud because he invented all this.  And he called it the OODA loop. Here’s his story – Boyd: The Fighter Pilot Who Changed the Art of War.

Where possible, I have used Boyd’s words directly, and give him all the credit. Here is a list of his words: observe, orient, decide, act, analyze-synthesize, double loop, speed, organic, survival of the fittest, evolution.

Image attribution – U.S. Government [public domain]. by wikimedia commons.

 

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Mike Shipulski Mike Shipulski
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