Are we Driving in the Right Learning Gear?

Which impact is relevant – now, tomorrow and in the day after tomorrow?

Yes, which questions are we asking ourselves to move impact to higher levels? and so which aspects of our performance of today are we ignorant to and missing out on?

Maybe we receive such a high premium on what we do, that we do not seek out these questions. To us it is perfectly ok to jump around “as need be”. We just hire people accordingly and fire them again like old horses when they burn out from peaks of overload and valleys of boredom, and we find it perfectly normal that new-comers “figure out themselves”, and so we enforce practices of feedback focused on individual utilization levels (efficiency) and “what is in it for me”-deal making.

On the other hand, our context may not allow the luxury of slow evolution, clumsy use of human potential (overworked and underutilised) nor a total lack of growth in used knowledge. Key to us is a high level of collective ability to move on opportunity. So we ask ourselves – team, service flow and whole business – questions on our inter-play, to operate in anti-fragile manners, deploy visible knowledge and service life cycle practices, and grow stronger from upsets in our system of service and by proactively tying onto emerging opportunity.

Whether we attend to it or not, we always operate under the influence of our collective learning habits. The “which impact is relevant – now, and in the future” is a challenge to both see and address the effectiveness of them. It is to both recognize and deploy the right collective learning gears.

Our current beliefs and practices of inter-play thus need not be our only options to drive forward. A classical way to provoke our minds on this is the maturity curve.

Picture 1: The Maturity Curve

Learning Gears of the Maturity Curve

At the start-up of any endeavor, sustainability or anti-fragility practices, seems to be ridiculous perspectives to bring in. We focus on demonstrating that our hypothesis of value cannot be denied.

Getting through to that pattern of customer impact – we understood their problem, we made the best performing solution on their problem, and yes, they will pay for it – and being ultra-flexible in jumping from one solution type to another to get to this outcome, is key to us. So typically we do not consider how we are part of a bigger pattern of learning and actually we want to fence off this “something bigger”-thinking, as we think and belief it is just stopping us or at best slowing us down.

Picture 2: The Linear Push Model

However, as soon as we arrive to that successful end point solution knowledge, then what? Now we face scaling problems – that is a backward looking knowledge transfer one and forward looking service life cycle one.

Problems which we did not experience till now, and so did not consider important. Now we realize our limits. We are highly dependent on the few we are and our heroic deeds. Indeed we are very fragile.

At that moment, we may regret that we had not built into our start-up the collective learning routines of our future, and so the ability to both differentiate and switch learning gears.

So what are these learning gears of the future?

They are basically all about our inter-play, that is our collective and integrated practices to“perceive and plan work”, “the focus of our feedback loops”, “our standards of shared knowledge” and “organisation of work”.

Picture 3: Learning Gears

Gear 1: Task Specialisation + Efficiency Driven + Fragile

Our collective habits of learning do essentially not exist in this gear.  We do not perceive any type of collaboration. On the contrary, everyone is focused on doing their own thing – in their own domain of work.

Work is something that is happening to us on an event by event basis. We are the passive receivers of it, and so there is no planning. Demand is just coming to us as individuals, and so we approach it, do our task and deliver on it reactively.

For the customer it means that she needs to know which tasks are needed to solve her service problem, and in which sequence, and then she needs to shop around, and engage one task master after another to get her full service need satisfied.

Performance is for task masters only about the doing – the Task done and further to iterate by oneself on what works for the event in question. The Task Master is ignorant to the bigger picture service need of the customer, and assume no complaints means a job well done.

As a consequence task masters consider learning and knowledge to be about Personal Achievement. The more I as task master do on the matter, the more I get to know on my knowledge domain (specialty or function) of work, and over time I may even be considered an Expert.  A highly sought for reputation to strive for in this learning gear.

The organisation of work hence is very much based on Individual Heroics within Types of Work. Each is expected to know and do as need be, and there is a massive feedback loop confirming to all that Heroics and standing out as individuals is what matters. Customers confirm this belief by always asking for the “right person(s)” to be engaged on their tasks aka the Experts.

In this learning gear most functionally driven organisations operate, and that even though the 1950’ies are long gone. It is amazing to experience, how many of us are still stuck here.

Perhaps I wonder, we just prefer this slow and clumsy learning gear, as that is how we learned to learn in school. Back then it was all personal, and we never learned to learn as a team or as teams of teams – so why now?

Picture 4: Functional Judgment Drives, Impact Learning is Ignored

On another perspective, then who – in 2018 – are happy with inter-play and feedback practices focused on tasks and output? That is just lame; to ignore customers of service and not seek learning about impact with them, right?

Newer generations do not accept this kind of non-sense, they know that both customers and team’s matter – change is coming.

Gear 2: Projects of New Ideas + Output Driven + Anti-Agile

In this gear we plan work as a sequence of jobs via a more or less formal – Project Process or People Scheduling logic. This may or may not include both a Solution Exploration and a Solution Exploitation.

A project begins via quite reactive Demand shaping practices, so when a customer request is out (i.e. typically from a senior manager), then that is the moment resources gets rallied up around it, and gets deployed.

Performance is about delivering the outputs of the Schedule within the customer specified Time Frame. Hence Output by Deadline is what matters, and that no matter how many projects run in parallel!

It is the job of a Manager or a dedicated Project Lead to do all the planning as well as drive home this type of achievement by influencing and rallying up all the right people aka experts to get it done.

The organisation of work is also happening by a Project Lead or Manager of Function. S/He coordinates and controls all the work, with more or less smart “inclusion-to-team aka group” and “bossy-motivation” methods.

Knowledge is not merely considered individual in this gear however. There is space for collaboration with various degrees of transparency on tasks, risks, time and timing matters, but alignment on purpose often sucks.

Tools take center stage, as they help inform on and coordinate tasks, risks and progression – what have we done lately and what is next – as well as Methods of faster completion of the individual tasks.

Consequently most projects are behind schedule, as all task owners tend to add a little safety time buffer to their time estimates, however still procrastinate the doing, so surprises always come in late or very late.

It is in these circumstances the Individual Heroic culture of the past learning gear kicks in again, boys become men and girls win a first time respect of the old guys. Weekends, Late Nights and Nights are put to use to deliver on the time expectations.

In totality, this learning gear represents the speedy drive towards something we later figure out what is. Choices of direction are not in the open, and so to question purpuse (all the whys) is not on, there is no time for that.

Gear 3: Service Flow + Throughput Driven + Robust

In this gear work is planned as a Stream of Work from Demand 2 Delivery – a Service Stream. It is designed and deployed with keen interest to enable delivery to takt, and to minimize handovers and disruptions to flow, as well as to allow for fast feedback loops on both the usage of current knowledge standards and improvement experiments.

Hence engagement in domain focused new idea projects, and cultures of clever functional colleagues and bosses deploying gear 1 and 2, we now at best plan as a second priority, and at worst frown upon and ignore completely.

Performance is about the Delivered Service Impact, and so our combined competence to deliver horizontally to promise. That is in terms of Customer Defined Quality, Timelines and Costs.

We now make use of Service Metrics to learn and communicate widely on our present ability to do just that, and as well as make use of collective review practices or ceremonies to maintain our knowledge standards.

At times we struggle with uneven demand flow, waiting time and blame circus on task bottlenecks, and so still in this learning gear Demand formation is pursued reactively, and it is a key cause of pain.

As we have formed collective means of feedback loops, and now surely realize the inter-dependent nature of work, we now approach knowledge as more than what is in the brain of an individual.

We design and deploy a Knowledge System of Service, and so visualize and make collectively used of our latest knowledge.  Shared Understanding, Agreement and Respect are key pillars to us. The vertical role of organisation is now clearly to grow re-usable knowledge, and so maintain and enrich it.

In terms of the organisation of work, we therefore no longer consider Task driven Functions nor Output driven Projects appropirate to set the drum beat of the organisation. We know that these vertical chains of command primarily want to advance their own kingdom of hot air baloons underlined with their keen passion for the latest new technology, tool or gadget – “so ein ding müssen wir auch haben”.

Instead we organise work via our Service Streams starting with its customers that it is all about helping. Each with a dedicated flow orchestrator – the Service Owner – who engages all in the stream to both maintain and improve our flow capability as a whole.

Picture 5: Impact Learning Drives, Functional Judgment Supports

We are now surely working on our service business system, not merely working in it, and so we are liberated from it or no longer being mentally imprisoned by it. We both see and challenge it.

Picture 6: A simple Business System

Gear 4: Service Impact + Balance Driven + Agile

Work is planned as a continuous balance between demand and our capability to supply demand, when it is really needed. It is not only perceived as a Stream, but also as an aggregation of work items in the Stream. Both today and in the future, in which we are able to make fair guesses on demand (forecasts).

We realize that this aggregate flow in our Service Stream is evolving like any queue, and so we:

* Frontload Capacity via WIP limits (work-in-process, not progress!) to avoid accelerating queue behaviors and so overload people with – ridiculous to the customer – waiting time consequences.

* Use Classes of Service to enable the frontloading to happen by customer risk types or cost of delay consequences – and so for us to service demand flexibly as real economic options.

* Action significant Changes in our short term demand backlog and our long term demand forecast (guesses). We do not wait for lead time changes to tell us to scale up or down capacity.

Because of this, we are able to make use of deferred commitment to the doing and delivery of specific demand. No more the policies of previous learning gears – like “Start now, Finish later” or “First in, First out” – which tend to destroy good people (overload / bore) and value (customer waiting consequences).

We have instead an ability to be both agile and proactive, and so allocate capacity to emerging opportunity, and plan for step change to capacity as we see customer demand for our services follow the natual s-curve evolution.

Performance and the focus of our feedback loops hence is about this balancing capability and so concerned with our complete economic system of service. Hence we deploy metrics of real Economic Prioritization practices including the probability distribution of our service lead times as well as lean principles of accounting.

These feedback practices depend especially on the depth and breadth in our Kanban Method deployment – the management method to visualize and work with service queue phenomenon as a collective – and our ability to differentiate guessing (forecast) with ambition, and assumption with drivers on assumption.

In terms of knowledge, our system of service is integrated with our customers. We have enabled upfront flexibility in demand intake, and our “commitment-to-deliver” practices are linked to the impact of waiting not to us, however to our customer. We really know how to deal responsibly with the ebb and flow of our business as a collective.

To orchestrate, we have Service Portfolio Owners working with Service Owners. The difference between the two is in their focus. The Service Owner focuses on: how a specific stream delivers? – i.e. the system of service and lead time consequences – whereas the Service Portfolio Owner focuses on: how our streams are deployed? – i.e. the queue behavior in and across our service streams and timing and capacity consequences accordingly.

Therefore our organisation has moved into a setup of Shared Services and Pools of Shared Resources. They help us to reconfigure quickly to changing demand as well as regulatory conditions, as well balance better the use of human potential with actual customer demand. Further, under stress, it allows us to swiftly follow shared emergency practices and so reduce likelihood of severe events and/or their impact.

Generally we have grown our collective learning to a high level of service orientation and customer impact thinking. We work consciously with our inter-dependencies and use them to the max impact.

Gear 5: Service Life Cycles + Adaption Driven + Anti-Fragile

Work is planned as a Service Life Cycle, and so our current service offering is realized not to exist in its current version for all eternity. Hence we reflect on the capability of our service improvements, by linking our ongoing System of Service with our evolving System of New Service Introductions.

We are concerned with both the different stages of our service in the market place (its classic s-curve life) and the balance between developing higher impactful service offerings to match the next market reality, and our capability to deploy these changes into our system of service.

We address this by planning a number of release windows per year – our change velocity – which we change only as we have a demonstrated ability to deliver. In essence the release practice creates a development cadence, and enables us to also approach our development opportunities and possibilities as a queuing system with economic consequences.

Our feedback loop focus – or Performance orientation – is clearly now on the real life impact (the effectiveness) that our service delivers to the service problem of our customer, and that compared to other alternatives of our customer. We are keenly focused on further enriching our understanding on their Service Problem and the evolution in it.

We differentiate therefore very clearly between vanity metrics – like the many covering specific jobs done, causing illusion about quantity (i.e. the more tasks done the better), and fit-for-purpose metrics – the few covering the service end2end outcome versus the needed thresholds for real customer impact.

In terms of knowledge, we now deploy a long term focus in our investments into our customers, and so allow for continuous experimentation to understand and deliver still better on their problem. Following, our knowledge focus is to update it sustainably to the next levels – again as a collective, not as individuals.

In this lies the key difference to previous gears – the move from point based new service intro practices – design then test – to set based new service intro practices – test then design. We now operate in the sweet spot between our business aims, our customer needs and our technical capabilities.

In a point based new service intro practice we develop a customer requirement set, and so set service specifications as specific as possible and as early as possible. Then we develop a few alternatives (concepts) and chose one for best assumed effectiveness, and so design decisions are made as early as possible, and project management is just something administrative to manage process compliance.

In practice we choose just one of the concepts to carry through the detailing and testing, to then fix what is wrong with it through multiple iterations until it works or gets discarded for obvious ineffectiveness. Further in case we make the service solution effective, we then run into the scaling trouble mentioned earlier. So we iterate also on our system of service, and that with high pressure to deliver yesterday. The innovation focus hence is merely on the new service concepts, not our complete business model.

In set based new service intro practices we focus on rough service specification targets to start with, and we then let details evolve with the project. Design decisions we delay as long as possible to get the latest and greatest trade off curve knowledge included. We test ideas to break the key curves before design.

Further, in the set based new services introduction system we have the role of a chief of customer success working at the intersection of several types of work – Requirements, Effectiveness, Feasibility, Trade Space and Affordability – and final service design decisions s/he only makes on known – not speculated – trade off curves.

Therefore project management in learning gear 5 is focused on managing knowledge growth into our System of Service, and so a very key customer of project managers is the ongoing and downstream System of Service.

The System of Service is never a supplier to the System of New Service Introductions. It is always the other way around. The customer is downstream!

The Innovation focus is on new service break throughs, and in essence concerned with combining knowledge in new ways and doing experiments on the very key – and so few – trade-off curves, and then to base all else in the new service solution on existing trade-off knowledge standards.

The organisation of work is now based on the Service Life Cycle perspective, and the Chief of Customer Success orchestrates the cadence of experiments, and set the tempo of service change via the dedicated release cycles, and so balance the experimentation on the key trade off-curves to the sustainable change capability in our system of service.

Trade off curves are the visual representation of service, and service stream physics and economics. They are our key means to understand, communicate, negotiate, train, record knowledge and conduct design cerimonies – and basically design quality into the service from its very inception.

Set based decision making makes our knowledge concrete, so that it can flow between areas and projects, and continuously be improved via experimentation, and it makes visible what needs to be learned to further converge.

Similar to the classes of service method deployed in the system of services in learning gear 4, a classes of service method is also deployed in the new service introduction system, and so we operate with different release cycles and practices for the different new service introduction classes it consists of.

A classic distinction of new service introductions is between costs of delay consequences of:

  1. New to the world (NPIs) services
  2. New Service Lines
  3. Improvements to Existing services
  4. Revisions to Existing services
  5. Repositioning of Existing services

With this, the fundamental shifts in our inter-plays from learning gear 1 to 5 is now complete, and we see our full system of play for the first time. Essentially emerging new service introductions and ongoing service offerings, are about growing and deploying knowledge about the service problem of our customer and impacts of its solution (s). Great services emerge from our inter-play, not from functional domain or individual ego drive!

New Service Introduction systems therefore focus on knowledge development accross projects, and the pull of knowledge into a cadence of new service introductions and upgrades. It means that because the beginning of any development work is now based on known knowledge and not intuition, we standardise design, confirmation of effectiveness and ramp up of usage. We avoid the costly iteration loops and waste of human potential that classical new service introduction work is so infested with.

Gear 6: Disruption + Needs Driven + Holistic

The 6th learning gear is special in that it is about challenging the mission of the whole thing we call work. Whereas the other 5 learning gears are focused on both the “what”, “who” and “how” of work, this learning gear is focused on the larger “why” question of work.

So work is now planned as Service Possibility, and is essentially about taking a step back approach on the ways our Service Demand is shaping up, and on the emerging social and technological opportunities, as well as our current models of business, and our assumptions and especially drivers of assumption.

What would a modern start-up do facing the service problem of our customer and these opportunities? Is our current take too narrow? As an example, if the customer need is movement from A to B, maybe our mission is neither to make and sell individual horse carriages nor motor vehicles running on fossil fuel, however instead planet effective mobility solutions. So – is it time to jump to the next s-curve?

The focus of our feedback loops is therefore on the drivers of these possible evolutions, and so the possibility to evolve much wider perspectives and knowledge growth on the service problem of our customer.

Maybe this includes experiments on moving us from a linear thought model of service business to a more circular model of service business, which includes moving us from eco-efficient (less bad) to a eco-effective (more good) practices, and so from more of a quantity to more of a quality frame of thinking.

Perhaps approaching our service problem from a life cycle perspective unearths totally different solution spaces for us, as well as enables our customer to plan in terms of life cycle outcome and costing alternatives.

Picture 7: Linear to Circular Economic Systems

The key knowledge drive in the learning gear 6, is hence to set flexibility towards our previously well-conceived definitions of service. It is about imagining new connections to emerge.

Some possible emerging practices are for instance – Industrial Ecology, Economy of Functionality, Re-use of Materials, Repair of Materials, Re-utilization of Solutions and of course further Re-cycling of Materials – and at the heart of it therefore evolving practices of Eco-Design.

In terms of organisation this learning gear possibly implies going from service chains to service circles – and so moving our organisation to new spaces of inter-play. It is about improving both our perspectives and relationships, on and with, present and future, customer and partners.

Organisationally this turf is the perfect one for the entrepreneurs who are willing to jump from the known past into the emerging future, and so mostly we do not bother much about the ongoing systems of new service introductions and ongoing service with these kinds of experiments. Most likely we therefore keep our learning gear 6 inter-play experiments in separate entities.

The Natural Context of each Learning Gear

The collective learning gears all have some natural contexts in which they typically are used in:

Learning gears 1+2:
in the start-up of something. Before a service really exist, and it keeps being our way of inter-play, if we keep letting our learning be focused on problems of the past – i.e. stay as the rat race of fixing.

Learning gears 3+4:
when a real service exists, for which there is a repeatable and possibly growing demand. When a real market competitive situation exists, wherefore we grow end2end perspectives on costs and a relative understanding on service effectiveness.

Learning gears 5+6:
when we consciously take a leading position on the service problem of our customer, and so invest in the problem, and not any longer keep our past solutions as the main focus. Deployment of the learning gear 6 is however rare, most businesses die, and never learn to master this gear.

Now, with the awareness of the collective learning gears, and perhaps having reflected a bit on them, how will you start up a new endeavor? Which learning gears will you make use of? when? and how do you shift gear during the time on the road?

We would begin with the inter-play beliefs and practices of learning gear 5, of course. That is to start from the end of all above, Right? Starting from the Customer Need you see an opportunity to get to own and possible lead, and so we would deploy a keen focus on impact feedback loops, combined with a core drive to build reusable knowledge, organised and deployed in service streams conducted with a team of service portfolio owners.

What do modern start-ups do? Right? They indeed begin from the end. They organise as tribes, not functions. They decide together not alone. They are collaborative in nature, not competitive. And so forth…  so is not time for change of our inter-plays of work before the survival of the fittest take over?

As Wiliam Edwards Deming once said: “It is not necessary to change. Survival is not mandatory”.

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