Tag Archives: logical connections

Diversity Boxes – ticking and talking

The Schumpeter column of The Economist took a run at diversity this week with the hypothesis that fatigue is big part of the problem. This fatigue appears to take different forms:

We hear about it far too much (Enough already!)
We hear about it but nothing changes (Not enough yet!)
We hear about it but what does it really mean (When is enough enough?!)

A look at the article’s comments section (which is always a dangerous move), reveals everything you need to know about the multitude of issues attached to the surprisingly complex word. Doubts and critiques expose some deep philosophical questions, as well as some statements that one is surprised to see in a written format (or not surprised, if you tend to read the comments section of publications).

A couple of things are clear about diversity:

This idea has been getting attention of late. (I recall a similar trend bubbled up around the multi-generational workforce in the last decade or so. Maybe this, too, will pass or linger.)
The word has many different interpretations and understandings
Consistent with 2, ideas vary on whether an organization needs it and, if so, how best to get it.

One of the ideas that the article attacks is diversity as a “tick-the-box activity. Fittingly, differing narratives surrounding “diversity” brings one critique that states the box-ticking organizations actually deserve credit because at least they are doing something!

Is it reasonable to say that the merits of box-ticking depends on the contents of the box?

There may be some consensus that filling the ranks with “the token [insert statistically under represented group member]” probably doesn’t work for anyone. (But I can imagine being challenged on that statement.) So, we should stay away from those kind of boxes.

Similarly, awareness building (especially when the topic is on heavy rotation in media) can also wear thin. So, maybe it’s not enough to “tick the box” on the Diversity Lunch & Learns.

If we are trying to prevent an over-reliance on predictable cognitive biases in important decisions, maybe we can tick the box on the presence of such initiatives as:

panel interviews for new hires
formal meetings of the senior leadership team to discuss and determine merit bonuses for employees above a certain level
determining tangible indicators to test the connection between our idea of diversity and our idea of performance

This is by no means an exhaustive list, nor is it a collection of best practices. Well-intended efforts to “do the right thing” can quickly get lost in the contentious world-view debates that risks making the situation worse. We are convinced in the merits of digging into an idea like diversity to understand how it fits into the business and find some clear ways to track the progress of distinct efforts even if that means ticking some boxes… but only the good boxes.

MONEYBALL – The Measure of Success Review

“..the first guy through the wall…it always gets bloody, always.” (John Henry to Billy Beane)

How things change
Getting people on board
Defining performance and changing expectations

Background:

This Michael Lewis story lays out what was the beginning of the rise of Sabermetrics: a new way of thinking about baseball. Previously, baseball nerd Bill James had a small cult-like following of people who always knew that mainstream baseball thinking and strategy were flawed. This group was enlightened but their wisdom was contained to the group of believers. The baseball establishment was simply not interested. In the early days of the new millennium, along comes Billy Beaned at GM of the Oakland A’s, whose particular problem makes it impossible to “play the game” as it is dictated.

“The problem we are trying to solve is that there are rich teams and poor teams, then there is 50 feet of crap, and then there’s us.” (Billy Beane to his Team Scouts)

The story plays out as Beane and his trusty sidekick Pete try to implement their strategy in collaboration with ownership, team scouts, team management and players. This challenge to an existing status quo and persistence in implementation are both fascinating and insightful, bringing real-world lessons to managers and leaders. Here is how the Money Ball story maps to the “collaboration game” framework.

Direction:

There is a great scene in the movie (quoted above), where Billy Beane lays out the problem for his team of scouts. The expression of this is only partial in this scene where he alludes to the fact that they have to run a shoe-string budget. Earlier in the movie he is very clear to state that rather than just “be competitive” or “not embarrassing” the objective is to win the World Series. Although “winning the World Series” is a point in time accomplishment, the general direction of “be the best” is important here and distinctly different from “be one of the best” or “not be the worst.”

Set-up – Rules and Constraints:

The link between the “be the best” direction and the specific Oakland A’s challenge stems from the small budget. The opportunity here is to create an understanding that “this is a challenge” rather than “this is impossible, why even try?” The former takes on the narrative of the wily underdog taking on the deep-pocketed establishment. Rather than moaning about not having enough money, the group has something to prove to the rest of the baseball world (think KC Royals of 2015).

Set-up – Measures and Metrics:

One measure for a professional sports team is summed up in the movie by the Billy Beane line “[Once you make the playoffs] If you don’t win the last game of the season, nobody gives a shit.” Close doesn’t count for those who want to “be the best.”

Spending within budget could be a constraint attached to a measure. There is at least one negotiation with ownership to release some extra money, so that constraint is apparently a little fluid. Conceivably as long as you can make the case for the necessity of this extra money in pursuit of the “be the best” agenda.

The tangible metric that is most revealing of the new logic is in how to evaluate potential. Enter the on-base-percentage (replacing the “batting average), which accounts for any skill in getting a base-on-balls, in addition to that of getting an actual “hit.” The logic flows as follows: You win games by scoring runs, to score you have to get players on base, so we want players who can get on base. (Sabermetrics had since evolved, and will continue to.)

In Sum:

To me the greatest relevance to the workplace is in the area of change overhauls that come down from the top. The CEO gets and idea in his/her head and tries to role it out through the organization. There are instances to “sell and tell” and there are some constituencies that refuse to buy-in to the new logic… and like any logical construct, the new way of thinking always has its flaws.

Can logic models work for you?

The “logic model” is a tool that is widely used in public and social sector initiatives. Like any tool, there are obvious on-target applications (e.g. hammer for inserting nail) as well as more creative applications (e.g. hammer to open a paint can). In all cases, the user is responsible for picking the right tool for the application. To me, there is relevance for the logic model in the private sector because this tool can expose assumptions (logical or not) and bring rigour to the thinking. Here is a quick primer on logic models, followed by some suggestions on if/how/when to use it for your business.

USEFUL VOCABULARY

Theory of Change: this is a set of fundamental assumptions that underpin a line of reasoning. This is often referred to in solving large social issues like homelessness or poverty. Relevance to a private sector context could be, for example, an ad agency president believes that to be successful, her team has to know our clients business better than they do. She believes sees her team as “providers of insight” rather than “meeters of needs.”

Logic Model: a framework that allows you to portray the specific linkages of your reasoning from the resources you expend to the final impact that you will have. The model takes into account the linkages between four fundamental components:

Inputs – These are resources that we control and choose to deploy toward the end objective. This is usually about money and time. Energy fits in here, too.
Outputs – This is what we create or produce or get from expending the “input” resources. This could be a report, the provision of a service, creation of some capacity, etc.
Outcomes – What we get helps us out in some way. This is the specific way in which it helps us out. We are better able to do something or something is improved because of the output created from the inputs.
Impact – This is the higher order calling of the whole endeavour. What did we set out to address in the first place? This is what we were after all along.

WORKING EXAMPLE

The thing about logic is that it can seem both commonsensical and obvious, while also seeming a bit opaque. To alleviate the latter, here is a quick example: Our agency leader (who believes that “provider of insight” is the way to success) might have the following idea.

Let’s get some of our junior staff to work on developing industry reports that capture both analyst information, as well as “chatter” from social networks. They will create an overview document as a summer project, and monitor/update on an ongoing basis. Our senior account people will refer to these before client meetings, and also share insights gained from the direct client interaction.

Breakdown using Logic Model:

Inputs – Junior staff hours in creating foundational document and ongoing monitoring (hours); Senior account staff time in inputting client insights (hours)
Outputs – The actual document, once it is created. The document is actually updated.
Outcomes – Senior account staff go to meetings with broad industry knowledge that they use to: (1) demonstrate knowledge to clients; (2) share value-adding insights; (3) initiate strategic conversations, etc.
Impact – Clients will use us more

Note: The understood “we hope” as a qualifier gets louder with each step of the model.

USING THE TOOL

Really thinking through these connections demands a good degree of effort and will: what do we want to “impact”? And how we will actually go about getting there? To illustrate the difficulty, recall the success of the ALS Ice Bucket Challenge. (Remember, this space is the sweet spot of the logic model). This was a huge success in gaining awareness (Mel B. did the challenge on America’s Got Talent!), but you may still ask: “So what? Are those afflicted by ALS better off? If so, how?” You can imagine that asking such questions without being labelled as “doubter,” “hater,” “loser,” etc., would be no mean achievement. This is an inherent challenge of such models. People don’t like to have the gaps in their logic exposed.

To use this tool effectively, leadership has to be comfortable explaining their logic (e.g. “provider of insight” beats “meeter of needs) and the followership has to be comfortable trying it out (if they don’t believe it in the first place).

Building the connections between the elements is an important exercise. You end up asking really good questions, for example:

Input to output questions: What are we getting for all these hours that we have put into research?

Output to outcomes: Is our new report, tool, capacity, etc. actually contributing to something that we are using, noticing, applying, etc.?

Outcomes to impact: Is our idea of the “means to the end” actually playing out? What do we really want here? What are we trying to achieve anyway?

This is the kind of thinking that goes into our “performance playbook” process to help ensure that the measures you are choosing hang together with the logic under which you are operating.

The good news is: I understand your thinking…

Yesterday, I caught a very brief segment on talk radio where a well-intentioned gentleman was explaining a solution that reduced energy consumption by turning off more lights at night. As a good interviewer does, Jerry Agar asked questions about the rationale for this endeavour. I was impressed at how quickly the guest (who I could not find on the site!) explained the connections that he was making, The train of thought is this:

If people trust each other, they are more comfortable in the dark.
One way to know that it is dark is that you can see stars (He actually said “the milky way.”)
So, the ability to see the milky way is a great indicator of how much people trust each other.
Let’s turn off the lights and start trusting!

Making connections between indicators and such fuzzy concepts as “degree of trust,” is a worthwhile, yet very difficult task. The impressive part of his explanation was not the logical connections, but the comfort that he had in telling another person how he had put it together.

My professional network contains some experts in philosophy who I will consult for a more technical critique of this reasoning than “Huh?!” In my humble opinion, this gentleman made a horrible argument, but I can’t stress enough the effectiveness of his clarity and willingness to reveal his thinking. A clearly explained whacky argument is easier for everyone to address than an obfuscated description that you have to untangle. The former, we know to ignore or, if we like the guy, give some very blunt critique. The latter takes much more time and energy before we get anywhere.

So, full marks for clarity. Let’s work on the logic,