Posts Tagged ‘learning’

Flow in an Agile environment.

30 March, 2017

Flow is the new buzz. Each of us knows exactly what flow is. And how it feels. It feels great! You probably have even experienced it yourself. Great! But flow in relation with work?  That is something else. It needs planning,  and changing work habits.

In my previous blog I started with the above paragraph. It triggered questions on what Flow is? Trying to answer this question took too many words for a small reply. So I made a blog in which I describe what I mean with Flow.

Being in “the Flow” means that what I do in that moment of Flow goes ”effortless”, “smoothly” and in a continuous cadence.

When I talk about Flow in a team setting, there are two views:

  • The team is in a mood in which it “effortless” and “smoothly” produces results;
  • The work items run smoothly from left (input queue or Product backlog) to the right (output queue). There are no inventories that block the flow of work, and work does not flow backwards (upwards).

The view on work that flows upstream makes people realize the unnatural aspect of it. Work, like water, always flows downstream. If not, then the (natural) flow is ‘broken’ and waste is created: “effort to bring the water of work upstream”.

So flow in our work environment is the continuous movement of work items in the direction of the customer. Never moving away from the customer. In each step value is added to the work items. We only add value that makes the customer happy. If not we pollute the water, add baggage to the work items that makes the customer not happy, the maintenance more difficult and the change of defects greater.

Flow as well means that the effort for the workers is evenly distributed and not ‘batch-like’. The work steps are in balance. No step is overloaded and no step is starving.

Flow in a kanban system aims to reduce work staying in inventories, as this creates waterfalls. With a real danger of dam busts.

Inventory typically occurs when we hit a bottleneck or constraint. Opposite it means that we avoid waterfalls and inventory by taking away constraints.

the team becomes more stable and predictable in their  deliveries.

So, from whatever view you look at Flow, it is a powerful weapon making your team more fun and more resultful.

How SenseMaking creates learning organizations by effective change programs.

8 June, 2012

The natural approach for effective change programs is full involvement of and guidance by all involved key-players. Combined with a natural learning approach this leads to effective continuous change programs and a learning organization.

What is different related to old-fashioned centrally and top-down managed change or improvement programs is the emerge of the outcome during execution of the change program. Based on the learning path, new nearby objectives are defined.

Sensemaking creates learning organizations in just 6 steps.

1    Entry criteria
Use the 6 steps only if your problem belongs to the complex domain. Obvious and complicated problems are bests solved by using standard solving techniques. See the Cynefin model for background information on the different problem domains.

2    SenseMaker design
SenseMaker® facilitates continuous, small and large scale, fine-tuned listening to all stakeholders (clients, employees, external (non-)experts). The design of SenseMaker is essential for a successful change or improvement program. A correct design ensures that the right information is distilled. An incorrect design provides not the information that the next steps need in order to be effective. It leads to frustrated stakeholders as their voice, thoughts and ideas are not heard or implemented.

3    Initial workshop
The initial workshop both validates the SenseMaker design and generates a vision of possible solutions. These possible solutions provide the first steps towards learning. Typically a Cognitive Edge method like Future Backwards is used to facilitate the workshop.

4    Experiment definition
The outcome of the initial workshop is used to define a first set of low-key-low -profile experiments. The costs and duration of each experiment is kept to a minimum. None of the experiments is expected to provide an ultimate solution to the problem.

Each experiment is described in the form of actions and indicators for feedback-signals that indicate positive or negative change. By generating additional context information, management is able to understand early (weak) signals. In this way initial actions that show promise are extended while negative indicators trigger recovery actions and choose of alternatives approaches.

5    Learning by experimentation
The initial experiments provide learning opportunities. Learning is generated both from the experiments participants and by the feedback loop continuous and real-time generated by all stakeholders using SenseMaker.

6    Emerging change
Outcome of each experiment is evaluated both by means of it’s direct outcome or delivery and by means of the feedback mechanism. Those experiments that both deliver on outcome and receives good feedback are re-evaluated for strengthening and to be continued. Those experiments that fail to deliver are stopped. Notice that learning may trigger new experiments.

Step 5 and 6 is a continuous loop. New problems or emerging insights will most likely trigger new experiments. A learning organization is created.

The above figure below shows a graphical view on experimentation in a learning organization. In the emerging process of learning, more and more practical knowledge is generated. This enables more stable experiments. By reducing the risks of failing experiments, the size (€) and duration (T).