Two things learned from CALMalpha

CALMalpha – the first (alpha) Cynefin, Agile & Lean Mashup – was interesting in ways both intended and unintended.  Too much of the latter for some, and I did struggle with it myself at times.  But after letting things settle for a while, a couple of valuable takeaways:

Lesson 1: sometimes we jump too quickly into model-building when we’d be better off spending time listening to what the data might want to say to us.

There’s some actionable advice hidden there for practitioners engaged in process work such as the building of kanban systems: depending on the context, consider not reaching for the process mapping tool right away, instead start with the simple thing of making the work visible.

This lesson might apply also to the process of community-building and I’m sure the irony isn’t lost on the event organisers ;-)

Lesson 2: designing for resilience means accepting a degree of redundancy or waste.

Nothing startlingly new there, but it’s a lesson that risks being forgotten by two groups, namely those driven by the elimination of waste and those with a narrow focus on value.  And it helps me to crystallise something:

My proposition is that systems resilient to variety (in the type and urgency of request) and variation (in size, for example) are not only more effective but easier to deal with, aligning the interests of the organisation with those of the customer, worker and manager.  Not only do we have the tools to help achieve this effectively and repeatably for many types of knowledge work, the apparent waste of non-urgent and even speculative work is key to both short-term predictability and long-term success.

Release cadence, lead times and cost of carry

I once led a team that made 8 releases a year, or one release every 6 weeks or so. To use the jargon, a release cadence of 6 weeks.  Not exactly continuous delivery, but at the time it didn’t seem too bad either.  We had a dirty secret though: we ran phases of analysis, development, testing and deployment (yes, this was a phase, not just an event) in parallel, and our true lead time (from commitment to deployment) was actually closer to 18 weeks.  Those releases accounted for only one third of the work in progress; the remaining two thirds remained very much in progress.

What was the cost of that hidden inventory?  The calculation is actually quite straightforward:

Assume a burn rate of $12,000,000 per year (that’s not the actual number, but it will do), or $1,000,000 per month.  An 4.5 month cycle time means that on average we have 2.25 months’ work or $2,250,000 in inventory on our books. Multiply that by a suitable rate (let’s use 30% – I will explain this in a moment) and we arrive at an annual cost of carry of $675,000.  That’s a serious amount of money, yet arguably quite a conservative measure what the business stood to gain from lead time reduction.

Why 30%?  It’s just a parameter, but two justifications for my choice:

  1. An appeal to the rule-of-thumb figure of 25% for the annual carry cost of manufacturing inventory, which Don Reinertsen in Managing the Design Factory suggests underestimates the cost of carry in design work significantly.
  2. Because a portfolio with a target rate of return of (say) 15% will on average be half complete; the remaining work should earn twice that, i.e. 30%. See A funny thing happened to my ROI

[Addendum You may have spotted (as I just did) that my calculation gives a cost of carry equivalent to your portfolio return divided by the number of inventory turns per year. Perhaps that's easier to understand than justification #2]

Not convinced?  Look at it from your customer’s perspective.  How much could it be worth to them?

 

Intangibles matter

Elroy Dimson (Emeritus Professor of Finance at London Business School, writer on investment strategy) recently wrote

Risk means more things can happen than will happen.

Perhaps I have been reading too many physics books lately, but this quote got me thinking of parallel universes as a metaphor for risk management. How much do we really know about the universe we live in now? Are there future universes out there that we should try to create or to eliminate, that way shaping our journey into the unknowable?

Evil Spock!
One universe to avoid

In Kanban, Intangible work items are those that affect our destination some indeterminate or distant time in the future. They’re uncertain (we’re dealing in outcomes that may never materialise) and hard to value, but their potential impact is sufficient to make the habit of these small investments a very good one to nurture.

This isn’t the first time I’ve linked risk management with Intangibles; see for example “Intangibles, value and risk (or: Portfolio thinking)“.  I return to the subject as part of an ongoing conversation with my friend and collaborator Jabe Bloom (@cyetain) who has kindly given in to my pleading for him to publish his “Space Shuttle” exercise.  Read about it here.

Tempting as it might be to focus mainly on eliminating downside risks, it’s important to understand that a healthy portfolio actively seeks upside risks too. Invest in your people, and one of them might surprise you. Product and platform investments might leave you better able to take advantage of market opportunities that are hard to see right now. And as I’ve argued before, not every process improvement should wait on the identification of a cast-iron ROI. Keep investing in the 4P’s of capability (People, Product, Platform, Process) and help bring those happier universes into existence!

If that’s too fanciful for you, I finish with this from Wikipedia’s page on Intangible Assets:

Competitive intangibles are the source from which competitive advantage flows, or is destroyed.

Intangibles matter; the worst risk of all might be to underestimate them.