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The (Post)ROI of Kanban - Part 4

Updated: May 5, 2020

In Part 1 of this series, with the introduction of some basic Kanban, we reviewed the economic benefits of transitioning from focusing on individual contributions to that of collaboration across a team. In Part 2, we saw even more quantifiable economic returns with the realization that teams also need to collaborate with other teams. In Part 3, the service-oriented approach to doing Kanban emerged, it was a significant demarcation point towards more substantial and sustainable business results - in short, it was a real Kanban sweet spot. If you haven’t read parts one, two or three of this article series, please read them first and see you back here shortly.

The success of the type of Kanban described in Part 3 is really good news since the more sophisticated Kanban described in this article is of a type few companies get to. This is mostly because getting to this level is limited by the maturity of an organization's leadership culture - the characteristics needed would include:

  • A focus on long-term business survival over tactical success

  • Success measured against meeting customer's needs vs competitor positioning

  • Both a curiosity to understand how the work gets done and the drive to do something about any gaps discovered

  • The patience to see through vision that is not always possible through a quick fix

  • A willingness to rethink how the organization is structured and makes decisions to minimize the risks of delivering fit services

It is this last point about decision-making that adds some irony to this ROI series; the Kanban practices at this level of business maturity quickly relegates the use of ROI as a decision mechanism to a much smaller role. Organizations at this level are not making decisions to make a quick return - their goal is more about being market leaders in offering their services as well as the ability to remain that way.

Risk Hedging and New Ways of Decision-Making

"It's easy to use ROI to differentiate between a bad and a good decision - the limitations of ROI become more apparent when trying to use it to differentiate between multiple good opportunities."

The use of ROI shouldn't be summarily dismissed, after all, it does provide for a way to filter through delivery options. It's unlikely sustainable to continuously deliver poor ROI products and services.

It's easy to use ROI to differentiate between a bad and a good decision - the limitations of ROI become more apparent when trying to use it to differentiate between multiple good opportunities. Having a volume of good opportunities to consider is a more realistic scenario for many companies, and so ROI is an incomplete way of making better decisions. Particularly at this level of maturity where we've already accepted that we will be working within our capacity limits: we can't say yes to every opportunity at the same time.

ROI as a decision-making mechanism is also a barrier to innovation as new novel offerings rarely have winning ROI characteristics vs expanding on existing offerings. The late Clayton Christensen documented this problem in his book The Innovator's Dilemma.

Decision-making at this level of maturity is more about ensuring service offerings are: fit, have clear alignment to a well-defined strategy, keep to capacity allocations and hedge any risks to the organization. The implications are that decisions are multi-dimensional in nature trying to achieve the right balance across a wide variety of organizational needs. A noncomprehensive set of examples of decision factors could include:

  • Capacity Allocation - Is the organization overweight or underweight in certain areas

  • Delay Risks (Cost of Delay) - How does delaying this opportunity compare against delaying another one?

  • Target Markets - Are there certain markets that are more focused on by the organization vs others

  • Innovation Horizon - What balance of opportunities are about current needs, future opportunities, and developing new markets.

A multidimensional decision making framework.

I go into how to use this in some more depth in an older article called How Much does Innovation have to do with Good Ideas?

Quantitative Analysis

At this level of Kanban practice maturity, we observe the ability to leverage quantitative analysis to better make decisions and make promises with customers.

This comes about through the development of two areas:

Capability Analysis - The discipline to capture delivery metrics for all services provided by the organization. This information allows for the development of a much more accurate understanding of the capabilities of each service. It allows for the development of models to allow decision-making on when to start or delay opportunities as well as predict their completion timeframes. Promises to your customers can now be reliably made, potentially in the form of SLAs.

Removing Delivery Delays - Through the pervasive use of the Kanban Method, sources of delays that make your delivery capability erratic or unreliable have been identified. Without going to details, these delays are contributing factors to the distribution of our delivery capability that can be "mediocristan", "extremistan" or somewhere in between; my colleague Alexei Zheglov describes this in more detail in his article Time-in-Process: How Do We Really Know?

Many of these delay risks likely run across the organization and may require cooperation across business functions and divisions. At this level of maturity, however, you have the culture required to address these systemic organizational issues. The outcome is both much more reliable delivery capabilities and a capability that is fit for your customers.

Combining these two factors we get both the ability to accurately use predictions to make good decisions and more often those predictions are good-news stories suggesting delivery performance within a threshold that is acceptable to our customers.

Organizational Feedback Loops

Bringing to bear our more reliable quantitative analysis and decision-making frameworks will require much more alignment between and across organizational services. Where previously Kanban feedback loops were about improving and maintaining a particular service's performance, we now scale this to performance across all services. This is the domain of the Kanban Cadences: Operations, Strategy, and Risk Reviews. Janice Linden-Reed gives a great overview of these and other cadences in her presentation: Building an Information Flow

The Benefits

In keeping with the previous articles in this series, some of you may be looking for a quantitative example to show the benefits at this stage. However you won't find one, and that is the point.

At this level of maturity, we aren't overly worried about ROI; it's become clear to organizations that running a business is about taking risks. These businesses focus on managing those risks so that the organization exposes itself to large upside risks (payoffs) and reduce their exposure to large downside risks (ruin). Their focus is on ensuring that the organization, at a minimum, continues to survive and preferably maintain and grow its prosperity at all times. If you need an ROI model however, my suggestion is to focus on the first 3 articles in this series, they already have more than enough to satisfy your business case.

At this maturity level, beyond the services offered by the company, a new capability arrises: the ability to quickly adapt to changes to the market. This capability allows the organization to cap risks quickly that could lead to ruin. It also allows the organization to take advantage of new opportunities that change introduces. This could be expressed by quickly bringing new services/products to the market and/or dialing up or down the volume of existing services.

The result of this capability is not services that are currently fit, but the ability to continue to maintain that fitness even in the face of unpredictable and rapid change.

In Part 3 we saw the exciting payoff of using Kanban to make your services fit. In Part 4, we went even further by recognizing that maintaining that fitness is yet a further capability we need to build. In doing so we go beyond profitability and develop an organization that may be built to last.

See you next time for Part 5, the final installment in this series, where we round things out with a look at the cost side of implementing Kanban in your organization.

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2 comentarios

Martin Aziz
Martin Aziz
04 may 2020

Great question Kyle. The impact of early quantitative analysis at the level of a specific service is actually already contributing to the lead time and throughput improvements shown in Parts 2 and 3 of this series. Particularly as they form the basis for high-quality feedback loops to inspect individual services (e.g. SDRs). There is no guarantee however that improvements in these services aren't coming at the cost of performance in other areas of the organization. Or if these particular services that are improved are the right offerings of the organization. In part 4, quantitative analysis has become a reliable capability not in a subset of services in the organization, but for all services. Offerings across and within all services can…

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Kyle Chandler
Kyle Chandler
04 may 2020

Great article. This leaves me with a question. In the quantitative analysis section you seem to suggest that organizations at this level of maturity (focusing on survivability) are only just starting to leverage inspection of capability (through kanban metrics / charts) and active detection/removal of sources of delay. Is this really the first time they start doing this? My understanding is that this happens (with varying levels of discipline) at the early stages of Kanban to help catalyze improvement needed to reach the more mature stages of Kanban. It would be great to get your insight.

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