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Jackeline Moura | Agile Coach Consultant | everis Brazil

Connecting Principles of Agility in Workflow Management and Work Systems

How certain are we at the moment? The current scenario of most organizations is uncertainty and instability. And that’s fine! But, what about in this context, are these companies adapting?

If today’s scenario is one of uncertainty and instability, a few years ago, it wasn’t so different, even though the challenges seemed different: companies were beginning to face large projects, complex solutions, and working software.

The best approaches and solutions used to respond to complexity were defining and following processes, plans, schedules, and massive scope specifications. The consequence of this: companies increasingly bureaucratic, rigid, and with increasingly complex and expensive systems.

In response to these problems and challenges, the 1990’s empirical and adaptive methods and processes, based on experiences and observations, began to gain strength. But did this solve all of the problems? No.

The agile movements’ focus was then to question and soften the weight of prescriptive methodologies and experiment with a new way of working.

Agile principles and practices do not prescribe how to make decisions, how to analyze the root cause, how to organize different workflows, but, with practice, necessary transparency emerges, in an accelerated way, and what needs to be adjusted in short cycles of learning and adaptation.

Systemic view in complex ecosystems

Companies of all levels and sizes are complex ecosystems of people, culture, systems, flows, and mentality. A systemic vision is the company’s ability to observe and identify the relationships and integrations of this incredible ecosystem.

For example, a system of work becomes more and more complex as organizations grow. The interactions between people and integrations between process flows and designs become more challenging.

With the growing volume of demands, it becomes more difficult for organizations to deal with the different expectations that arise from all sides: new products, solutions, market demands, deliveries to customers, etc. The complexity increases when these diverse demands and expectations are lost and enter a waiting state in large work lines.

These are some of the consequences of this scenario:

Silos: Areas and teams solving only their part of the process, precisely because there is no practice of observing and understanding how the flows behave and how the activities of each one interfere and integrate with the whole.

Fire extinguishing” practice: Usually, a massive crisis occurs when incidents, defects, and unexpected interruptions of solutions and products arise. Probably the capacity of the teams and areas are not known, and therefore it is almost impossible to decide what to prioritize to focus on the immediate solution. Meanwhile, the way the final customer sees the company, which is directly linked to its delivery speed and solution/value, is compromised.

Decision-Making: Without the vision of the whole, decision making (strategic, tactical, and operational) is not assertive. It is quite common to get involved in initiatives where expectations are very high around results. Still, we run into rigidity, confusion, and disorganization around basic workflows, teams, and systems in the first decision to be taken.

Observing the life cycle of demands

Observing workflows, identifying inputs, outputs, steps, and capacity is the first step to bring out the whole’s vision. The prioritization of what will be developed and delivered is another important factor. But prioritization is only effective if comparing demands with each other is possible, considering minimal value, urgency, complexity, risks, and effort. Or perhaps, when the demands of products and solutions are prioritized, they do not correspond to the clients’ real needs.

· Start going where it happens (Gemba): Observe the flow limits from the birth of a specific demand, the next steps, the bottlenecks and impediments during the process and when it is considered as finished.

· Visualize the flow: The flow should be visualized as the flow should be, considering improvements as a step that should be initiated later. Only from this it is possible to identify the types of impediments, wastes, and improvements in an incremental way.

How does the flow behave?

· Where do different demands come from? From which criteria are they considered suitable to be developed?

· What is the nature of the demand: added value, market demands, system improvements, incidents, etc.

· How long does this demand wait to be prioritized? And how long does it take to go through the whole flow and finally be delivered?

· Are there bottlenecks in the flow stages? Which ones?

· What is the delivery pace of these demands? Is it sustainable, or is there a lot of work overload, generating extra costs and team dissatisfaction?

· What is the size of these demands? Is there a lot of size variation in the same flow?

· Is there a pattern in the flow, or is each one creating its queue? Is there collaboration around the same flow?

· How are the teams organized around this flow, and how is the work pulled?

· In addition to these initial questions to identify the flow behavior, evaluate other aspects such as learning, waste, innovation capacity, goal unfolding (e.g., application of OKRs), encouraging transparency, decision-making, and clarity of roles and responsibilities.

· Co-creation is essential, i.e., the more everyone is involved in analysis and discussion, the more assertive and less ambiguous flows will emerge. On the other hand, the focus should always be on how to improve; otherwise, discussions are easily biased by general grievances and complaints about the work.

Stabilizing the Flows

Now it’s easier to identify and create your own work patterns, systems, products, and solutions.

“Where there is no standard, there is no improvement” — Taiichi Ohno.

Use metrics to identify patterns: To identify waiting, delays, and flow rate, it is important to start with basic metrics that require the information already available:

· Lead Time: The time it takes for a demand (any work item) to go through the entire flow, from its birth to its delivery. This is the time perceived by the final customer, regardless of the waits and inefficiencies in the workflows. Start with the practice of recording the demand entry date and the delivery date.

· Throughput: Consider the number of demands delivered in a given period, days, weeks, months, etc. The flow of a flow (delivery rate) is directly linked to the behavior of the flow.

Making decisions to improve the flow

While metrics are incorporated and tracked, decisions can be made more accurately — based on data. When organizations don’t understand how the flows behave, the fastest decision is to increase delivery capacity.

How? By increasing the number of people on the team, for example. But the result is usually increased operating costs and queues continue to grow. On the contrary, the basic management practices suggested here are generally more effective ways to achieve and establish increasingly fluid and continuous flows.

· Reduce the size of the queues: Avoid keeping single queues, that is, an available flow where all and any demand is pulled, no matter its nature, characteristic, priority, or size. The teams organized around this flow will not deliver at the same rate, given the variations in complexity and urgency of these demands. Visual separations in the flow can be used to represent these different themes. It is easier to establish which team pulls each item, which should be the limit of the work in progress (Working In Progress), and other criteria.

· Reduce waiting time: Once the flow is identified, the steps that generate the most waiting will become more and more evident. Usually, validation/approval steps are big bottlenecks because these validations are from other areas or teams. There can be waiting at any stage of the flow, and therefore a more significant challenge can be found here.

· Reduce variability: Equalizing the size of the demands is also very important. While the team is overloaded trying to deliver high demands, the queues are getting bigger and bigger.

Conclusion

Transparency, inspection, and adaptation are the main pillars that should guide the journey of continuous improvement in organizations. Transparency as the basis for knowing how to face the problems to be addressed and support decision-making at all levels. Inspection as the observation of how the workflows through the different levels. Adaptation as the basis for encouraging learning and improvement through mistakes. An organization that does not enable continuous learning through its mistakes and successes loses the opportunity to adapt more quickly to changes.

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