A Spoonful of Sugar helps the Analytics Go Down

Utilize narrative structures to give senior leadership the detail they need to make smart decisions.

This is a story within a story. Since those can be confusing, let me clearly state my hypothesis, up front:

> THE STORY: In business, especially complex operations, the “narrative” is a pivotal tool for successful communication to senior leadership

> THE STORY WITHIN THE STORY: As an example, I present a narrative tool, called “Drew’s Traffic Cube,” that I utilize often to think about, present, and discuss the interplay of Digital analytics in my business

Scaling Information for Leadership

The human brain is an amazing analytical machine, no doubt. But based on the idiosyncrasies of our evolution, there are some pathways into analytical processing that are shorter than others. Understanding that all of this exists on a curve, science has discerned boundaries for the volume of discrete bits of information that we can input and process at one time.

In business, we often need to input and process large numbers of variables in order to accurately model and execute our work. For those of us who are individual contributors or middle managers, this comes with time and effort. As we gain facility with a body of information or data, an adequate amount is transferred to tacit knowledge that we can understand and operate creatively upon the big picture. Awesome for us. But what about leadership?

Senior leadership needs an adequate understanding of these variables to make the right decisions about where to focus resources, attention, and cash for the betterment of the enterprise. Only in exceedingly rare cases, however, can the CEO spare the time and bandwidth to grok those attributes at the same level of detail that you have in order to carry the analysis to its current point. Thus, the information must be compressed such that it is digestible by that leader. Let’s define a few key modes of compression, just to set the stage:

• CONTEXT: Information without context can be misleading at best, and dangerous at worst. A few moments or phrases to establish the big picture helps to position this issue within the larger universe and fills in a bunch of the background.
• VOLUME: How much actual data must be presented to the leader to articulate a clear point? Does the data in question lend itself to rolling-up without unacceptable degradation of fidelity? Not all data sets do…
• ACTIONABILITY: How can we present that leader with an easy ability to take action? Presenting a limited number of options, along with pros/cons may be the best way. Or, perhaps, more of a Chinese Menu approach that allows her to mix/match attributes. How do we clearly state those attributes which defy quantification, such as risk?

Let’s not think about this as ‘dumbing it down for the boss’. The boss is plenty smart, in most cases. But she’s also responsible for way more stuff than just your little analysis, and needs to spread her attention around in an equitable fashion.In light of that scenario, developing and maintaining strong skills/structures for translating information from the granular level at which it is generated and synthesized, to the coarse level upon which key decisions are made, reveals itself as being pretty damned important to the health of our business.

Narrative Structures

One methodology I have used with great success for this scaling of information is to convert it into narrative structures. Stepping back to cognitive theory for a moment — our brains are evolved to have particular affinity for stories. Before the written word, narrative structures were literally the only storage mechanism available for information across time. For that reason, narratives can be useful vehicles for conveyance of complex information into easily digestible chunks. The ‘spoonful of sugar that helps the medicine go down’, as it were…

I use the term ‘narrative’ loosely here, to represent any story, model, or other structure that translates the data into a common, shared — sometimes even colloquial — format. By doing so, we provide the leader with the ability to map our data to relational concepts already established in her own brain, helping speed familiarization and understanding. Analogies are great, as are defined use cases and small vignettes. Anything to get the numbers/issues off the page and into the real world where people operate in three dimensions. My usage of this technique is so prevalent in my own work that once a colleague created the term, “drewnalogy”. As in, “Hold tight, here comes another ‘drewnalogy’ [eye roll].”

Drew’s Traffic Cube

Here comes the story-within-a-story… By way of example, I’d like to present a narrative model that I have utilized for many years in my own work running Digital Operations for a number of major enterprises. [EDIT NOTE: if you’re already bored, feel free to bail now. I’ve already presented the larger point about scaling information for leadership utilizing narrative structures — whether you agree or not — and the post doesn’t include any additional chase scenes or CGI action sequences.]

Digital technology is endowed with a wealth of analytical feedback to match any industry of which I am aware — and flattens the vast majority of other industries in that respect. Thanks to modern, first- , second- , and third-party tools, we are able to learn a tremendous amount about the activities, interests, behaviors, and [even] identities of the people utilizing our Web and mobile-based tools. Information isn’t the problem. Too much information is.

In order to make sense of all that data, and convert it into a model that allows us to understand, collaborate, and action upon it, I have generated the following model. It focuses on three key accessible metrics of Digital technology, their interplay where the health and growth of our business is concerned, and the logical model of a cube.

Quick Birdwalk: Area and Volume in Geometry

This is the math[ish] bit. I’m not a math guy, so will keep this short and include pictures to help my own people follow along.

You may recall from high school geometry that the area of a shape is calculated based upon the lengths of its sides. As these lengths are increased, the area increases. Important to note that this growth occurs in a linear fashion.

That’s cool, and intimately understandable for most humans. Even down in the low-brain where we do so much of our minute-to-minute thinking. “Longer sides make for a bigger shape — CHECK”.

When we add a third dimension, to talk about cubes and volumes, it starts to get more interesting. This, because an increase in the lengths of each side of the object no longer creates a linear progression. Instead, growth occurs at a cubic rate. Hence:

This curved rate of growth can have big implications when it comes to things like loading cinder blocks into your SUV at The Home Depot, or making enough popcorn for all the kids on the sofa. And, due to these real-world experiences, most people have a reasonably-clear tacit understanding of the role that a multiplier plays where volume is concerned. And it is that existing bit of knowledge that we will take advantage of in our narrative.

Defining the Cube

In order to help senior leadership, understand the implications of changes in the analytics that define our Digital business, I utilize a model of a cube. I’ll describe my model below, but by this juncture you understand that isn’t really the point. The idea is to take a messy, data-heavy body of information and press it into a model that is innately familiar to the audience. Here’s mine.

AXIS: Scale

In Digital technology, we use the term “Scale” to refer to the reach of our tools within the population in question. Scale answers the question of “how many” people are utilizing what we make available to the world. Growing Scale means bringing more people in the door. The specific analytic we utilize for Scale is Unique Visitors, though others may be more/less appropriate.

AXIS: Engagement

In this model, engagement refers to the things those users do when they come to our Digital tools. How many articles do they read? How long do they stay? How many products to they view? How much time do they spend using faceted search? How often do they come back within an average month? Engagement is about how we make the most of each user’s visit, and is often measured through analytics such as Pageviews per Unique Visitor, Session Time, or shopping cart activity.

AXIS: Conversion

Conversion refers to the models with which we monetize the activity of the user on our Digital outlets. Are we making that user available to advertisers, based on their interests, her interests or [hopefully], both? If so, how many advertising messages are being presented to that user during the experience? How many is too many? Are we coaxing that user into a purchase funnel, and therefore trying to remove as much friction as possible from the decision/action to buy? All of these are analytics of conversion.

AXIS: Revenue

Revenue is represented by the volume of the cube. In fitting with the constraints of this model, Revenue isn’t something you can put your hands on, directly. Instead, its size is determined by adjustments made to the three axis that surround it.

Wielding the Model

This is where the power of the narrative structure becomes apparent. Utilizing the mental model of a three-dimensional shape, we can begin to understand how adjustments made to the defined axis have the potential to impact revenue. The model becomes a shorthand in support of our discussions and collaborations. Since we’ve come this far, let’s take this model for a quick spin to see the kinds of dialogues it can engender.

How to grow Revenue?!

Among the most vexing questions in all of business is, ‘how do I grow revenue?’ To the extent that this model represents reality, the answers to that question become readily accessible — at least at a strategic level. “Increase revenue by increasing Scale, Engagement, and/or Conversion”. More excitingly, if you can increase all three, your growth has the potential to manifest in a greater-than-linear fashion. “It’s great if we can increase our Scale by 7%. But if we can get each of those new users to consume 11 pages, instead of the 8 we are currently at, it’ll have a multiplier effect!”

Mutually Exclusive Choices

Business is full of mutually exclusive choices, and this model helps me to communicate those where managing a Digital operation is concerned. The interplay between Scale and Engagement provides a handy example. In a content business, the kinds of things we do to increase Scale and Engagement can actively foil each other. To increase Scale, we broaden the focus of our editorial footprint, attempting to entice a more general audience. Increasing Engagement, alternatively, often means narrowing the focus of our content, such that the enthusiasts utilizing our tools find more that speaks directly to them and therefore consume more of the content. Thus, driving for an increase in Scale can inadvertently trigger a decrease in Engagement, and vice-versa. Conversations like these can be made dramatically less confusing by leveraging the three-dimensional object model and talking about the implications of growing one axis as opposed to another.

Lady Luck is Fickle

This model can also help us when times are tough. Sometimes in our business, a small discerned erosion in footprint can have revenue implications well beyond what might be initially expected. The model helps us understand that, if we are losing Scale, Engagement, and Conversion at the same time, our losses accrue logarithmically. Our business is falling into a hole and we need to make some difficult choices to arrest its descent. If Scale and Engagement are suddenly out of our control, what tricks can we play with Conversion to make up the shortfall? How long can we do this before suffering unmitigatable consequences?

Conclusion

If you’ve read this far, you have certainly picked up the point of the post. Business is complex, and middle managers need to find ways to cut through that complexity to effectively service senior leadership. Among the strategies for doing this is the utilization of narrative structures. In a Jungian sense, we can grab hold of context that already exists inside the minds of our audience, mapping our own data to those in order to maximize speed and efficacy of metabolization.

How about in your businesses? Do you regularly utilize narrative structures to enhance your collaborations? Any that you might share with the rest of us? Any horror stories of becoming trapped in the mental models created by these narrative structures and remaining blind to attributes not covered in the model? I’d love to hear more about these techniques in your own business.

Originally published at https://www.linkedin.com on December 1, 2017.