Learning from Lessons Learned

In a recent post I had mentioned how lessons learned would become visibly useful when it became possible to substantiate the impact of lessons learned.  Where knowledge is closely integrated to business operations, it becomes easier to track the use of such knowledge and the impact it has had on the business – either in terms of improvement in business performance measures, a positive impact on process measures, or measurable impact on people metrics.  However, the challenge usually lies in the fact that lessons learned are seldom directly linked to performance measures.  More often than not, they remain as lessons identified in the knowledge repository, with no measurable or tangible evidence of such lessons actually being put in use.

With the proliferation of enterprise social collaboration, does it make the task of tracking the dissemination of lessons learned any easier?  Is there any way of finding out if the lesson learned from a previous project or experience has been implemented elsewhere?  Or has some similar work been carried out in any other part of the organization which is quite similar to the experience based on which this lesson was learned?  A community of practice is probably the first place one is likely to check for such instances.  When groups of people with similar interests share a platform in which discussions happen, it is quite likely that such topics are discussed, and more evidence can be gathered about such lessons.  Evidence of a lesson learned elsewhere which crops up in discussions in a community of practice is one of the first signals that a lesson is being taken seriously, and is likely to find implementation elsewhere in the organization. 

Tracking the network of people associated with a particular community of practice can provide pointers to how well the information has been dispersed across the organization.  Where formal learning structures are integrated as part of the enterprise social network, it is also possible to associate these lessons learned to the formal learning structures.  For example, a simple survey or a quiz usually evokes a lot of interest among the community; and the response can be an indicator of how well this lesson has been picked up across the network.  Further, a link to the lesson where the answers are incorrect, or even providing that as a reference is likely to increase the people who will get to read this.  However, this does not necessarily guarantee implementation of a lesson learned.  All we can inference from such statistics is that there has been sufficient dispersion of this message across the network.

The package of practice is the other likely place one can possibly evidence the impact of lessons learned.  Where a process or a procedure has been changed, being able to trace it to the influence of the community, and to the set of lessons learned that caused the change in process or procedure is not hard to trace.  More often than not, where there is sufficient automation of processes or where processes are executed through standard software, it is quite easy to track the change request and be able to associate it with the appropriate lessons learned.  In such cases, we have far more solid evidence that a particular change in the process or procedure was initiated because of the lessons learned.  The actual implementation is itself traceable.  A word of caution: since we haven’t linked it to actual business performance, we still don’t know whether this finally did result in some positive improvement to the business result.  Nevertheless, we are still ahead of the game in terms of at least being able to quantify the impact of lessons learned to process improvement and / or people improvement.

At the end of the day, the ability to influence a large section of the network is itself going to result in the creation of the tipping point where positive impact will automatically start to flow.  The key then remains as to how enterprise social collaboration can be made an effective tool of engagement such that it brings in more people to contribute and share knowledge.

Would love to hear about actual experiences in organizations where impact of social collaboration has had a positive impact on the business, and how it has been measured.

Putting Lessons Learned into Action

Acronyms and jargon have a wonderful way of locomotion - especially around my being.  They manage to enter the ear and leave through the mouth, silently, stealthily without a trace.  And as I continue to struggle with AAR, LLR, RCA and the like, I came across yet another term - A3.  Fortunately, this time around it was not an acronym, but just a hook to hang a process on.  A3 is a process followed by Toyota to record process improvements, and the name is derived from the paper size they originally used to write these reports - they probably still do!

So, the topic is about how organizations learn from their mistakes, and ensure that these lessons stay with the organization.  Most quality programs statute an improvement process which usually starts with something called the Lessons Learned. This is usually a stand-alone document or gets associated with a Project Legacy Report or something similar.  The intention, of course, is to record the lessons learned during the execution of a project, or in the process of identification and resolution of a problem or issue the organization was faced with.  However, in most cases, this gets recorded more as a matter of following due process and usually gets stored in some remote location, never to be retrieved again.

In a "social enterprise" - one where people in an organization are networked, have easy access to each other, are able to have conversations on ideas, insights and issues and knowledge is easily transferred through people or content - making the switch from tacit to explicit rather effortlessly - it ought to be easier to make lessons learned available across a larger cross-section of people.  However, what is more important is to ensure that this lesson is put in action, institutionalized - either through a process improvement or a skill improvement program and results in tangible benefits to the organization.  This can happen only when knowledge (or rather the use of knowledge) can be measured.

Lesson Learned Reports also have a rather tedious method of being static and inhibiting exchange of ideas - even after the report has been prepared.  This can be avoided by making the report preparation itself a dynamic process - one which happens as the problem identification occurs and the solution is identified.  And when such a process becomes interactive, and happens in a collaborative environment, chances are that there are a lot more people following the progress, and therefore stickiness or ability to recall the lesson is higher.  Also, in the process of tracking progress, there are other teams of people who are simultaneously experimenting with the solution and coming up with modifications and suggestions.  The dynamic nature of such a solution has the ability to impact a practice (or a process) making the institutionalization of such a change much quicker.  The impact of such a change is also quickly shared across the organization and becomes measurable.

How are lessons learned (LLR) or After-Action-Reviews (AAR) conducted in your organization? Share your feedback on how good this tool is in causing business improvements.

Making sense of chatter - the knowledge manager's role

“In a post-Cold War era of ‘openly available’ information what you need are observers with the language ability, with understanding of the religions, cultures of the countries they are observing. Inman thought we needed fewer spies and more ‘slightly batty’ geniuses”

– From “What the dog saw”

As we observe organizations from the perspective of Knowledge Management maturity, the ones lower down the scale are still struggling with the problem of making information available, while the ones that have gone past that stage have a different kind of problem – one of information overload.  These organizations that have implemented core solutions and sophisticated business intelligence applications have a new problem to deal with – how to make sense of all the information that is being pushed out to them.  One the one hand you don’t want to set off alarm bells at every trough or dip in a trend graph because of an over-sensitive intelligence system; at the same time you don’t want to be caught napping because you have made your trigger-points less sensitive.  Many a time we are able to connect the dots only post-mortem; perhaps a lesson learned a little too late.  And with Big Data and the rest of the talk about integrating noise from twitter, linked in and what-have-you…this problem is only going to get bigger.

Knowledge Management is full of such ambiguities.  How do you trust decision making tools that are based on probabilistic inferences based on incomplete and fragmentary information? Or would you rather wait for evidence-supported narratives that perhaps reduce your ability to prepare a response in time to avoid a disaster?  Is it possible for organizations to create a system that will allow fragments of information to be deciphered – to see a pattern even as it starts emerging, and then prepare an appropriate response? Can organizations become adaptable enough to be able to create an ecosystem that will allow such information to flow so that such analysis is possible? Is the knowledge manager supposed to be this “slightly batty” genius who can enable this?

The year 2009 was when we first heard about Cognizant becoming a serious threat to the Big Three.  A Forbes article of 2010 explains the rise and rise of Cognizant to a position where it has even overtaken Infosys.  While there is quite a detailed note on the strategy adopted by Cognizant to become a dominant player, what has probably been left unsaid is the preparatory work it has done to metamorphose into a serious challenger.  The integration of so many acquisitions, the transformation of its culture, and the transition from a process-driven organization to a knowledge driven one has surely played a significant part. The subsequent years of continuing dynamic growth seem to suggest that the decision to use Knowledge as a primary driver of growth was indeed one of the key factors responsible for such a quantum jump in Cognizant’s fortunes.  In 2007, together with the young and dynamic CEO, the Chief Knowledge Officer - the “slightly batty” genius, R Sukumar charted a course for Cognizant 2.0 – their integrated and pervasive, collaborative knowledge management system.  I have been following his impassioned speeches on Knowledge Management, and what little is available in the public domain s probably sufficient to provide evidence that they have a very vibrant and impactful KM system in the organization.

Sukumar is one who I would like to call a truly “batty genius”; the idea of bringing on someone like him to a role that is generally considered a “put-to-pasture” function was path-breaking and indicative of the importance accorded to the knowledge management initiative.  Although many companies already had some form of knowledge management going on, most of them were under the garb of quality initiatives; Cognizant took it a step further by making it a prime driver of strategy.  And being someone who had been in the system for quite some time, he was the kind of person who understood the culture of the company and could speak the language.  He had worked in the frontline and knew the pains and pressures; it is this kind of a person who is best suited to don the mantle of a Knowledge Manager.  I wonder if Sukumar can give an inside perspective that goes just beyond the tools and technology aspect of Cognizant 2.0, and provide an insight into the role the KM team performed. 

In a sense, the role of a Knowledge Manager in an organization is quite similar to what countries do in war time (or even peace now) – to follow closely events occurring in countries that can be potentially detrimental to their domestic and international interests.  Where there is a veil of secrecy surrounding such operations, a corporate entity requires a lot more openness.  The information that is “openly available” needs to be transformed to insights; this transforms the function to into one of collaboration – one in which the knowledge manager enables the organization consume the extant content, while facilitating active conversations that will throw up interesting insights.  And like top secret government organizations, the process of integrating the insight into the strategy becomes a centralized role.  However, the information, the analysis and the insights themselves are crowd-sourced, in other words, obtained locally from the people who are best informed.  The knowledge manager has a team of knowledge stewards who constantly scan the “chatter” while enabling subject matter experts ensure that the entire organization receives value from the content that is available in the knowledge repository.   Their role becomes one of interpretation and analysis of these conversations, engaging with the organization in enabling these conversations take on new meaning, influencing conversations that drive the organization towards their knowledge-driven strategy to the end objective of achieving sustainable competitive advantage.

Does your organization have a Knowledge Manager?  What kind of structure do you think best suits an organization – one in which information analysis is centralized and becomes the function of a specialized team? Or one in which there are silos of information analysis, but a centralized function that is responsible for transforming insight into learning and then to knowledge?

#disclaimer: I have no personal or professional interest in Cognizant, nor do I hold any shares in this company.   My fascination for this company primarily stems from their involvement as one of the key participants of the KCommunity in Chennai. 

Quest for the KM Chimera

"Is it a bird? Is it a plane? No! It's Superman!  Like the mythological Chimera, Knowledge Management seems to be made of many different aspects of business.  In turn, people perceive it differently - interpreting it in as many different ways as they perceive it.

Knowledge Management may be simply defined as a set of strategies and practices used in an organization to identify, create, represent, distribute and enable adoption of insights and experiences. Such insights and experiences comprise knowledge, either embodied in individuals or embedded in organizations as processes or practices.

Any tool or system that facilitates one or more these components will likely get categorized under the broad ambit of Knowledge Management.  For example, if we were to look at the various tasks, then the tools that will get covered under this would include:

·         Identify insights and experiences - Business Intelligence, Business Analytics, Data Mining, e-Discovery, Search Engines

·         Create, Represent and Distribute - Content Management Systems, Taxonomy Classification tools and methods, Social Collaboration tools et al

·         Enable adoption of insights and experiences - Learning Management tools, Business Process Management tools, et al

A few of them perform one or more of these activities in a very narrow slice of the overall business - like Customer Support and Service, Customer Relationship Management, or Infrastructure Management.  Most others work best in one of the above with the ability to feed into the other aspects of the definition - for example, BI enables identifying insights, but the rest of the activities are mostly carried out outside of the scope of a BI tool.

Although I have listed Learning Management tools and BPM tools under the third aspect of KM definition, in reality these happen in a very passive manner, disconnected from the definition of KM itself.  BPM tools, especially are good at defining business rules and changing processes that can cause improvement in performance, but will not be able to relate to the actual experience or insight that caused this change.  Similarly, LMS tools can impact learning and enhance competencies in people but will not be able to measure the performance enhancement.

Any organization looking on the path of operational excellence will look at integrating one or more aspects of this into their process and people improvement initiatives.  However, depending on the level of automation of business processes and the KM maturity, their choice of Knowledge tools will vary. Depending on the urgency and level of maturity all of these applications will typically end up vying for the same slice of the budgetary pie (as opposed to the budget available for core and peripheral applications that are more transactional in nature)

A Knowledge Management tool, should ideally straddle all three aspects of the definition either in collaboration with other tools, or as a stand-alone tool.  The ability to adopt insights and cause a shift in the way the organization works at the process and people level, is really where Knowledge Management will become a key driver of Business strategy and Performance improvement.

What tools do you know of, which serve one or more of these functions in a seamless manner?

Teaching the elephant to dance...

In his book "Who says elephants can't dance?", Louis Gerstner, the CEO of IBM who is credited with its massive turnaround towards the end of the last century, talks about the painful process of re-engineering the organization, as part of the process of the turnaround he effected.Reading that part reminded me of the very similar problems that much smaller organizations face...ones who have grown rapidly, and suddenly find themselves in the 'A' league.  They grew rapidly because of the entrepreneurial spirit of the core team, each person vested with the responsibility of making that division or department matter.  This is especially true of the new age companies, those in the IT, Telecom and mobile segment.  Equally suddenly, they begin to discover that what brought them to this point is not good enough to take them further.

We have experienced a similar situation as a smaller company getting acquired by a larger one, and suddenly having to cope with a vastly different cultural and business environment.  The freedom and agility that made us successful and brought us to the attention of the company that acquired us suddenly became our bane; this was now perceived as chaotic and "unprofessional".  The challenge became how to continue to remain nimble and agile while still being able to leverage the strength of the larger organization.

The question that remains is how do we teach the elephant to dance....or I would prefer to re-phrase that to "How do we not become elephants"!!!  Can these organizations continue to remain agile, retain their entrepreneurial DNA, and yet draw immense strength from size?  Does that size actually contribute to any of their strengths?

As an organization that develops and implements KM solutions, we have often been confronted by this question.  I believe the ability of an organization to retain its core values is essential for its long-term survival and sustainability.  As an organization grows in size, the traditional methods in which knowledge was shared and decisions begin to change.  The oft-repeated "water-cooler" insights are no longer possible.  However, these very insights that occurred in informal conversations (tacit knowledge) is what created the possibilities.

The organization needs to find new contexts to communicate, be related, and stay connected.
Insights that were possible because of conversations, and because the data needed to analyse them were smaller have now grown in order of magnitude.  How can these still be parceled into smaller chunks that make them still conversation-worthy, and therefore create the potential for insights.  How can managers be prompted to look at information, explore and discover lessons that they can apply.

Organizations can continue to be agile and entrepreneurial if the knowledge that they can harness from being a larger unit can be accessed easily, collaboration among these smaller units is available for the larger organization to benefit from, and it becomes possible for the organization to sense and respond to threats and opportunities without having to resort to militarization of their culture - uniform processes, monolithic systems, cumbersome workflows.

A framework that enables collaboration and sharing of insights, captures and transforms these insights into learning and promotes the institutionalization of a mechanism to leverage this learning will ensure that organizations can continue to appear chaotic, remain competitive and stay agile...and grow.

Would love to hear your views on this.