Some thoughts on change management

No pun intended, but the broad topic of change management has great currency in the business world today.

What people typically mean when they say "change management" is some structured approach to understanding the stages humans go through as they understand and cope with change.

This is prescriptive if you are attempting to manipulate or engineer human behavior, so it has great relevancy to Industrial/Organizational psychology. Thus it finds its way into the business world.

Like software development lifecycle models, there seems to be a change model to fit any mood or mental predisposition. I've seen these three commonly referenced in business world, and I'm sure someone with better Google fu could find even more change models:
In each of these change models, the important and useful takeaway is that the model defines and codifies some phases of acceptance or resistance to change. When the business world talks about change management, they usually mean something prescriptive, along the lines of:

Step 1: Adopt a model of change. Hire consultants or highly paid experts to train people to understand said model of change.
Step 2: Help people move from one stage of the change model to the next. (characterized, for the sake of my allusion, as "Eh?")
Step 3: Profit! (Usually for the consultants.)

In the interest of full disclosure, I will now reveal that I am a highly paid consultant, and that I sometimes make money helping organizations cope with change.

This is all interesting and good, but... this model of merely defining and facilitating adoption of change leaves a high-order problem unsolved.

That unsolved problem can be most figuratively described as "the death of a thousand little cuts."

A visual and graphic metaphor I've used to describe this part of the change management problem follows:

Imagine you are a surgeon, as am I, as are five or six of our best friends. Further, imagine that we have a patient in front of us. I have to do an appendectomy. You have to do a repair to the patient's ankle. Someone else is working on a shoulder repair. Someone else is elbow-deep in the patient's lower intestine. Each of these surgeries is survivable. Not exactly out-patient, but not a big deal these days. The patient would be expected to survive each of them, individually.

The problem comes when all of us try to operate on the patient at the same time. In that world, the patient certainly dies on the operating table... Too much surgery all at once, and the patient simply can't handle it all.

Leaving you with the mental image of that poor patient, stitched and stapled from stem to stern, we'll move back to the business world, and change models. The high-order bit that seems to get missed in all these model of change management is the apparently novel and foreign idea of change metering.

Back to my metaphor -- what would happen if we each did our respective surgery serially, giving our patient time to recover and heal between trips to the ER? It would cost a lot, but our patient would survive.

In my experience, humans can only metabolize so much change at a time. Further, it doesn't really matter what the change event is -- they are all psychically disruptive. They all require the psyche to adapt and to absorb the change. They all start a journey through some phase model, ignoring which one you like best.

What's important isn't knowing what to call the phases. What's important and mostly missed is understanding the capacity of the system to absorb change, and metering the rate of change so that the system doesn't get overloaded.

So, by long way of introduction, I've got a model I've been using to describe Change Metering.

First, you have to think about what you can do to people. In business, there is a fairly finite list of factors you can change within an organization. I break it down into 7 categories in my little model:
  1. Location - Where do you do your job?
  2. People - What do you do for a living?
  3. Team - Who do you work with?
  4. Leadership - Who's in charge?
  5. Technology - What tools do you use?
  6. Process - What modes and methods are the norm?
  7. Policy - What behaviors are mandated?
Within that 7-fold spectrum, you can have small, medium, and large change events. A few example change events follow:
  • Technology - Small Change Event: You get a new version of MS Office.
  • Technology - Medium Change Event: You switch from MS Office to Star Office.
  • Technology - Large Change Event: You switch from Windows to Linux.
  • People - Small Change Event: You switch jobs to a new but similar role.
  • People - Medium Change Event: Your job changes, and some responsibility goes away.
  • People - Large Change Event: You get promoted to a new job, with enhanced responsibility.
These are just examples, but you get the picture... Each change event in your work life, or in the work life of your organization, will fall into these seven buckets, and will be graded on this scale.

(Oh yeah, Small = 1 change point, Medium = 3 change points, Large = 5 change points.)

So, if you have followed me so far, you can see that using this model, you can easily build a multi-dimensional array of change, over time, over a team of people. It might look something like this:

(click to make this big enough to read...)

Now, as the table shows, you have a change score for every "significant" event that has happened to this team, over a few months. The next bit of this requires some hand-waving, but will work for the sake of explaining why change metering is so important.

Assumption 1: People absorb change at more or less the same rate.
Assumption 2: People can absorb change in about 6 months. Irrespective of the change model you choose to use, or whether you even have a change model in mind, in six months, people will have pretty much gotten used to their new (compiler, operating system, campus, boss, coworker, etc.).
Assumption 3: Change absorption is linear. (Why linear, you ask? Because it makes the math easier.)
Assumption 4: Though these units are arbitrary, accumulating more than 12 of them is bad.

Making these assumptions (and with the caveat that you can make up your own numbers, as soon as you get your own blog), you get a visual representation of the change absorption rate in this small team. (again, click on the image to make it big enough to read)

This can be immediately prescriptive:

As you can see, the whole team is going to be pretty stressed out in June and July.

If you were an executive manager and you were interested in, for instance, launching a big new discretionary initiative aligning your work norms to a new process model, you may want to wait until Q3. That slight pause in your roll out would prevent your change from overwhelming your team, and would give your initiative more mind-share and a better chance at success.

If you were the manager of this team, you should note carefully that you've got poor Amy in a state of perpetual flux. You might want to pay extra attention to her performance, and offer assistance as she absorbs her new role, new responsibility, and all the other change you've thrown at her.

In summary, change metering is more important than change modeling, but few people I've ever worked with have grokked this fact. If this model helps you, use it. Contact me via e-mail to negotiate royalty fees.

And to help amortize the cost of my graduate studies in philosophy, I will close with a quote from Heraclitus of Ephesus:

Πάντα ῥεῖ καὶ οὐδὲν μένει

Nothing is permanent but change


Ken Stone said...

As always, very insightful observations and suggestions. I know linear models make the math easier, but I will offer one proposed amendment:

Those "large" change events have more of an impact, on more team members, and therefore have more of an exponential effect. Since I have neither the time, training or patience for developing or maintaining complicated mathematical models (leave that for the highly-paid consultants, when I posses that other magical dimension - budget), when I adopt Tom's model I will rate the events as:

small: 1
medium: 3
large: 8

and keep my eye out for that 12-14 range in any 6 month period.

Of course, that's based on my own rating and bias of what's small, medium, or large in my own world of technology services business development and management.

Thanks for the diversion, Tom!

Business Outsourcing said...

This is nice and very thoughtful post. I dont know that it will works or not but its a way ofcourse...

Outsource Data Entry .