Process and Public Service Renewal

by Kent Aitken

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Just a quick post today. I was on the road most of August and am still mostly just catching up.

A few weeks back I wrote about The New Nature of Process, the idea that that organizations are at a pivot point akin to industrialization. But where that revolution occurred by standardizing and repeating processes for material goods, we're looking at standardizing and repeating processes for human learning in the context of complex problems. All optimized for efficiency, fitted within governance and business cycles.

(Albeit with a broad view of efficient. Sometimes expensively sending a nurse practitioner to someone's house is, in the long run, more efficient than optimizing the process within the hospital they'd otherwise visit.)

Let's call it standardizing processes for exploring and solving complex problems. At the time I considered it an interesting idea, a possible trend. But after thinking about it for a bit I realized that if it's true - that is, if we're just getting started but can get far better - it would assuage the doubt I feel about public service renewal. Even the elements of it that I personally support and suggest.

For instance, in the past I've wondered if a public service characterized by trust, decentralized decision making, and engagement is unrealistic or undesirable. If such a state only works well in marginal cases, such that the success stories for that approach actually represent most of the fertile ground. Or, after Chelsea highlighted some of the more negative possibilities of loosened hierarchy, I wondered if the style of management I considered ideal was too unreliable across a critical mass. That it would work well only if it was the only thing managers had to worry about (it isn't). Or take Hugh Segal's recent take in the Ottawa Citizen, about the need for stronger managers, less management layers, and more leeway for frontline decision making.

I generally favour these approaches, in a vacuum. But the real world is messier. However, if we can significantly and reliably accelerate employees's sensemaking of complex environments, such approaches may be very manageable in the real world.

And the sensemaking tools are there. How to map a network of stakeholders, how to help them (and you) understand each other, how to suss out side effects of policy, program, and service decisions. The question now is one of optimization and repeatability.

The Underappreciated Impact of Digital

by Kent Aitken

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I still read articles that discuss how digital technology and connectivity are transforming democracy, unlocking avenues for communication and governance. Entirely, totally true. No argument. But there’s an angle that seems underappreciated to me.

Most articles talk about it as we have found these people interested in what we’re doing, and we can connect to them, so we will. However, the far more interesting thing to me is that these people were always here, we just didn’t know how to find them.

The digital era both revealed the problem - that our decisions touch far more people than we once realized, and can impact their lives significantly - and presented a solution.

But, two things:

First, it's a solution, not the solution. Just because we can find people through digital means doesn’t make it the default interaction channel forever. There’s a reason online communities hold meetups. We need to know when to deviate from digital.

Second, recognizing that in the past we had a measurement problem, underestimating the breadth of our impact, we shouldn’t assume that we’ve solved it completely. Rather, we should be deeply concerned about who we haven’t found yet. Even for those on the easy side of the digital divide, not everyone raises their hand.

We always talk about digital technology as a solution,  but the problem that hyperconnectivity revealed is at least as interesting. This is the underrated impact of digital technology: not that it enabled government to connect and engage, but that it made us realize that we should have been doing so all along.

Note: this is an argument I've partially made in different forms before (See: Complexity is a Measurement Problem, People Act, Technology Helps, or Collaboration: Overhyped and Underappreciated), so apologies if this is old hat. But I wanted to explore this particular angle of it, and it'll play into a forthcoming deeper dive on this idea from last week: The New Nature of Process.

The New Nature of Process

by Kent Aitken

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In a recent report on the next frontier of digital technology, Accenture created a model of the long history of challenges that have faced management.

http://www.accenture.com/us-en/Pages/insight-looking-digital-being-digital-impact-technology-future-work.aspx 

In short: the industrial era was characterized by a transition from individual craftsman and artisans to large-scale processes, and this transition was enabled by repeatability. A worker didn’t need to know how the factory ran to screw part A into part B, and if he left, a replacement could be trained incredibly quickly. This was the age of Taylorism, of precision and measurability permitted by process and structure.

 

Throughout the last century we’ve transitioned into an economy far more based on knowledge work (see Deloitte’s assessment, below), which meant the industrial management style ran into a crisis of rigidity, the solution to which was adaptive processes. Judgment, discretion, if-then statements, case management.

http://dupress.com/articles/the-future-of-the-federal-workforce/ 

However, for senior executives ultimately managing a variety of adaptive processes, the problem then became one of complexity. There’s too much going on, it’s too hard to understand, and the performance reports that are so useful for widgets-per-second are far less revealing.

 

Accenture suggests that the solution to complexity is in digital. Specifically, “smart digital processes”, which would feed decision makers key information exactly when they need it. My response is: maybe? In some cases? It seems the more plausible answer is a return to process - which is happening all around us, albeit which a crucial difference from the Taylorism of old.

 

 

Process in the Knowledge Economy

 

There's a common thread among the emerging approaches to governance. In his equation for today’s public policy, Nick highlighted several, including design thinking, behavioural economics, and public sentiment. We could add the field of facilitation, the practice of public participation, and innovation labs to them mix. All of which are hugely reliant on defined processes. 

 

The key difference is that the interim goal of the process of old was to remove the need for learning, whereas the process of today is designed to maximize the speed of learning. At the end of this post there are some links to example process kits: if-then guides to, essentially, helping humans understand other humans and the systems they live in.

The end goal is the same: scalability and repeatability. In this case, it’s repeatably, reliably solving unpredictable, emerging, or complex problems. We’re on the same arc as the first graph, but for a completely different organizational paradigm.

 

So the challenge for management becomes a new, grander problem of complexity. Where executives have been struggling to manage adaptive processes via industrial-inspired organizational designs, they’re going to be overwhelmed by managing a variety of learning processes without significant changes in management style. In some cases the if-then flow will be impossibly complicated, and in others it’ll need to be thrown out the window. A single node in a hierarchy will never be able to understand each process, only the principles behind them.

What's in it for Us?

 

We need to do it. It’s where the performance gains in a complex environment will come from. I’ll exapt an HBR article about how our personal learning curves regularly plateau. Here’s the graph, with learning on the Y axis and time on the X axis:

http://blogs.hbr.org/2012/09/throw-your-life-a-curve/ 

Success comes from knowing when to jump to the next learning curve, which is incredibly hard at the outset but maximizes the speed of progress.

Embracing this learning curve will be cost-effective in two ways. First, there’s evidence that consensus-building through learning processes costs less in the long term than making and defending decisions (which will apply to both internal management and policy/program governance). Second, in the latter part of that learning curve we’ll reach a level of sophistication that allows economies of scale:

• We’ll be able to reliably pull from a menu of processes and adjust to new situations, rather than starting near scratch every time
• We’ll be able to recognize when we can leave these learning processes to citizens, businesses, and NGOS, and govern accordingly
• We’ll be able to share and teach approaches broadly

Returning to Accenture’s claim, organizations have run into a problem of complexity. Particularly for governments, however, I don’t buy their claim that the answer is in smart digital. Instead, I think we have to recognize that in many ways we’re back at the beginning, worried about about scale and repeatable processes. Just very different processes.

 

Example process kits:

http://www.involve.org.uk/blog/2005/12/12/people-and-participation/

http://labcraft.co/

http://stepupbc.ca/explore-your-career-increase-collaboration/idea-navigators

http://www.mindtools.com