Many businesses are unconsciously generating more and more technical debt (backlogged engineering work) related to the workflows and the data that they use to get work done. A large amount of this technical debt is being generated at the crossroads of data governance and regulatory compliance, as well as data management and business agility. In many cases these businesses are unaware of how that this technical debt is building up and that their business risk is increasing as a result. At the same time, business inefficiency is growing in step with it. All they know is that getting things done within the business chains is becoming more and more difficult. They are not getting full visibility into what is happening within their business, with their customers and the supply chains that they use.
As business agility authors Steve Pereira and Andrew Davis summarize in their ‘Flow Engineering’ book: “Organizations are now so large and interconnected that digital dependencies tie us in knots. We’re drowning in a sea of data, yet we struggle to leverage it to make improvement decisions. Organizations are tantalized by the promise of radical transformations (cultural, digital, Lean, Agile, DevOps), but these often devolve into rebranding and renaming the status quo rather than bringing about real change”.
Since digital technologies have taken off successful businesses have continued to grow, to buy other companies, and to expand into new countries and new markets. Mobile technologies caused the first big surge in the amount of business data being generated by them. Now in the last 2 years another surge in the amount of data being produced has dwarfed the prior surge caused by the earlier takeoff of mobile technologies. This much larger growth in the amount of data generated is being caused by the amazing leaps in computing power, networking, ML and AI that have occurred.
Magnifying this problem is that businesses, especially older ones, have often not fully absorbed the companies they have bought, nor standardized their processes and tools across the company. This has increased the problems with silos of data in different forms developing within companies. This in turn has increased the complexity of getting work done and increased the inefficiencies. This complexity is a direct result of the different processes, toolsets, data formats and storage, and data management and access methods being used.
These issues can be addressed by businesses:
- Putting a focus on monitoring, measuring and visualizing their business workflows in real-time.
- Using the Flow Framework and Flow Engineering to help businesses to visualize and measure the workflow processes and process dependency chains to expose bottlenecks and inefficiencies.
- Use the workflow specific visualizations and the metrics visualized and measured to guide focus and investment decisions.
- Improving the data governance and data management used within targeted workflows and to lower business risk and increase business efficiency of the workflows targeted.
Research shows that ~30% of the human brain is dedicated to visual processing, which is part of why data visualizations are such a powerful information summarization and communication tool. The more complex an organization and its workflows the harder it is to see how localized activity contributes to the overall flow of work and the ultimate delivery of business value. Collaborative
Flow Engineering (and Value Stream Mapping that came before it) are both a series of mapping exercises that result in a data-based visualization of workflows, their bottlenecks and their dependencies. Using Flow Engineering practices allows you to focus and align your efforts to achieve a valuable target state, develop a shared clarity on the current state, and establish a flow of activities toward delivering that preferred outcome.
The Flow Framework and Flow Engineering are a lightweight method for teams to improve flow throughout their ways of working. At the heart of this method is understanding the team’s real goals, looking at how they currently work together, and then ideating on possible flow improvements. It is designed to connect the dots between an unclear current state and a clear path to a desired target state. It’s an open, adaptive, and engaging series of practices that can take you from complexity to clarity, from friction to flow.
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