In the book “Competing Against Luck: The Story of Innovation and Customer Choice” by Harvard Business School professor Clayton Christensen; the core concept of the “Job To Be Done” theory is introduced which is hugely relevant for enterprises wanting to leverage collaborative team work in creating value. The theory stresses that in order to drive organisational product, service and process excellence; we need to focus on alleviating the forces of anxiety, inertia, substitution and resistance across both the customer and employee value chain. Christensen articulates a mechanism to achieve this by firstly creating “specs” that define what outcomes and values are required in order to lead to customers or employees firing old methods, solutions, products and services and adopting new ones. In doing so, the product development team (as an example of a department vested with solving consumer problems) will be satisfied as they have induced consumer adoption either by bringing non-consumption into consuming contexts or working on incremental product and service innovation. Christensen states that “The circumstance is fundamental to defining the job (and finding a solution for it), because the nature of the progress desired will always be strongly influenced by the circumstance”.
This is important as traditionally, managers usually follow one of four primary organising principals in their innovation quest (or some composite therefore) being product attributes, customer characteristics, trends and/or competitive response. The challenge here is that these are not bad or wrong but they are essentially sampling of the most common and are insufficient and therefore not predictive of customer behaviours. In this article, I allude to how the Bioteaming action rules across the Organization, Execution and Connectivity Zone facilitates the dynamics required to solve the ‘job to be done’.
ORGANIZATION ZONE – POROUS MEMBRANES (OPEN TO ENERGY CLOSED TO WASTE)
Bioteams are open to energy and closed to waste. More on this can be read here. Therefore, in environments where front line sales teams are directly engaging with prospects and customers to consume and transact where the product set is heavily tiered and augmented, the firm is essentially aiming to cater for undershot consumers.
By offering features and addons that the product team have created; its crucial to garner and facilitate front line intelligence back to the product design process because a key feature in catering for undershot consumers (whom hold willingness to pay more for enhancements along product and service dimensions that matter most to them) is to provide integrated experiences opposed to specialised ones. It may very well be that the front line have identified non-consumers and this is core to new product and market innovation strategy. These consumers typically hire someone else to do the job for them and the front line is presented here with a unique conversational opportunity to understand the ‘job spec’ of the job that these consumers need to get done.
In doing so, they are invaluable assets to the organisation and should be supported by a methodology akin to what is known in Bioteaming as ‘Porous Membranes’ so that self organisation ensues and knowledge is passed back to the departments vested with service and product manufacturing.
This methodology can improve project management and an academic paper presents a specific case to answer the question: May project management benefit from the application of new theories and tools of software and communications based on animal behaviour.
EXECUTION ZONE – TEAM BASED GENETIC ALGORITHMS & NATURE’S INNOVATION FRAMEWORK
So how do teams adopt to the functional, social and emotional complexity of the ‘job to be done’ whether it be finding product improvements, service or process innovations? Broadly speaking, we need to understand that CoreCo (the current state and business) contains specific elements of organisational DNA and NewCo (the desired state or new business model) needs to effectively forget, borrow and learn in tandem with the core mindset. In order to implement this within the innovation cycle across enterprises, we firstly need to understand how Nature’s teams have evolved and exhibited strong collaborative team work forces through experimentation, mutation and team learning sessions.
Nature’s teams solve problems using a trial and error process called genetic algorithms. In the computing science context this is a technique based on evolutionary techniques. The mechanics of this approach is rooted on creating a population of new solutions derived from genomes (DNA) by random mutation. Various selection criteria are applied to pick the best solutions that are then ‘mated’ to create a new batch’. This process is continual through thousands of cycles until optimal solutions are eventually produced (iteration and multivariate regression).
In summary, they firstly breed new potential solutions; evaluate how effective they are and pick the best ones before breeding new solutions from the best ones and continuing to do so until the solution is optimum. The evolutionary nature of this may make this process inherently slow; however natures most intelligence living systems have found a way to achieve accelerated evolution through ‘intergenerational learning‘ through the power of language and inter species knowledge transfer. This is apparent where the British Buetits mastered the ability to peck open milk bottle tops that the mil men were delivering to the door steps of homes in the UK in the 1950s whereas the British Robin never mastered this skill as a species even though they had the same degree of intelligence and language as the Bluetits. Despite being every bit as innovative as the Bluetits and having the ability to essentially peck open milk tops; Robins are territorial birds and do not flock and hence did not pass on this skill to their community. Bluetits move in flocks of 8-10 birds and operating in this way facilitates learning and the transfer of it through the entire species through social propagation. This gives the species more options for competition and survival rooted on the premise of the team based genetic algorithm.
READY-AIM-FIRE VS FIRE-AIM-READY
The application to organisational and human teams takes an appropriately different approach than Nature. The traditional paradigm of Ready-Aim-Fire is a diametrical contrast to Nature’s Fire-Aim-Ready. In order to implement the elements of genetic algorithms in an effective and meaningful way and leverage off the framework that Christensen inlays in the jobs to be done theory; enterprises need to create a culture where individual failures are seen as essential building blocks for eventual success. This in turn will enable people to participate, reflect and learn – thereby ‘forgetting’ what contributed to failure in the first place.
In Bioteams, every member of the team is required to nurture team intelligence and constantly look out for threats and opportunities. These need to be instantly communicated to all other team members through a small but complete set of messaging protocols. Collectively, the ability to nurture front line intelligence and garner ideas from all participants in the enterprise is important to turbocharging innovation and working towards getting jobs done!
The diagram below outlines a simple process, “Get-Me” that a Bioteam can use to facilitate rapid learning using the biological method. This method is iterative and allows rapid formulation of ideas which can relate to any facet (product, service, process) and focuses on the three dimensions of any enterprise improvement initiative. These three dimensions are people, technology and process. Altogether, using this method will lead to:
THE BIOTEAM CONNECTIVITY ZONE – USING TOOLS SUCH AS SLACK AND MICROSOFT TEAMS
Microsoft Team channels can be created where members can post via any device (desktop, tablet or mobile) conversations which can be commented against by others. The use of group chats can also be used to behave like a Bioteam by being ‘Always On’ and sending information ‘in situ’ using simple vocabulary that can be then garnered to derive a more coherent user story map of the innovation initiative. Using slack channels can also work here as well as using threads in the channels (and emoticons) to second or build upon ideas that are working out or are pre-cursors to the next stage in the product, process or service development cycle. What’s powerful about these tools is its ability to be supported through multiple devices and functionality that allows tagging, searching, broadcasting and reminders. Here is an excellent article on how to organise your communication in rings or groups so that anciliary teams can also get involved in the conversation. This should be considered when using Slack or Microsoft Teams enterprise wide to engage front line teams with product development or executive teams for the innovation capture process. The idea after all is to work towards becoming a super intelligent organisation, bridging the divide between technology and people and operating in the middle. This is known as Augmented Intelligence.
CONCLUSION: INNOVATION, MOBILITY AND GAME BASED LEARNING
In conclusion, enterprises will always face a mystery of the middle scenario when trying to implement innovation efforts. The effective ‘circumstances of struggle’ will always exist whether it be in a product, service or process – and by definition; customers must fire some compensating behaviour or sub-optimal solution in order to adopt new products, services or processes. Here, the word ‘customers’ spans the full spectrum and are internal to the firm as well as external e.g. within project teams, departments, front lines, middle office or executives. By learning from Nature, we can introduce frameworks that inspire rapid prototyping and collation of ideas that will be the catalyst for the next big product, service or process innovation. At the end of the day, its very important to adhere to the mission of getting the job done and doing it in a focused way (by engaging all members of the core and outer teams) is the only way to break inertia and resistance forces against change and present a the right kind of innovation blueprint.
Organisational teams need to be able to mobilise ideas and nurture them thorough a systematic and iterative process that inspires information sharing and distributed authority. Large enterprises with multidisciplinary teams that are interacting in a matrixed style structure or even those that are operating via task forces should simulate innovation strategies and new market development in game based learning tools where the nexus of personality clashes and politics is effectively broken. Ken Thompson in this article puts forward a poignant point of reference across the four key stages of simulations being planning, design, testing and execution – all of which resonate strongly with principals of the ‘get me’ innovation capture mindset and Nature’s genetic algorithms framework.
About Max Bhanabhai
Max Bhanabhai is a bioteaming practitioner, author, strategic innovation and change management consultant. Max collaborates on Bioteams with Ken Thompson (The Bumble Bee). For more information on this important topic checkout Ken’s book – “A Systematic Guide to High Performing Teams (HPTs)”