The vast majority of analytics efforts are expended on problems that are tactical in nature. That’s not necessarily wrong. Tactics get a bad rap, sometimes, but the truth is that the vast majority of decisions we make in almost any context are tactical. The problem isn’t that too much analytics is weighted toward tactical issues, it’s really that strategic decisions don’t use analytics at all. The biggest, most important decisions in the digital enterprise nearly always lack a foundation in data or analysis.
I’ve always disliked the idea behind “HIPPOs” (short for the “highest paid person’s opinion”) — with its Dilbertian assumption that executives are idiots. That isn’t (mostly) my experience. But analytics does suffer from what might be described as “virtue” syndrome — the idea that something (say taxes or abstinence) is good for everyone else but not necessarily for me. Just as creative folks tend to think that what they do can’t be driven by analytics, so too is there a perception that strategic decisions must inevitably be more imaginative and intuitive and less numbers-driven than many decisions further down in the enterprise.
This isn’t completely wrong, though it probably short-sells those midlevel decisions. Building good creative content takes… creativity. It can’t be churned out by a machine. Ditto for strategic decisions. There is never enough information to fully determine a complex strategic decision at the enterprise level.
This doesn’t mean that data isn’t useful or should not be a driver for strategic decisions (and for creative content too). Instinct only works when it’s deeply informed about reality. Nobody has instincts in the abstract. To make a good strategic decision, a decision-maker must have certain kinds of data to hand, and without that data, there’s nothing on which intuition, knowledge and experience can operate.
What data does a digital decision-maker need for driving strategy?
Key audiences. Customer Journey. Drivers of decision. Competitive choices.
You need to know who your audiences are and what makes them distinct. You need (as described in my last post) to understand the different journeys those audiences take and what journeys they like to take. You need to understand why they make the choices they make — what drives them to choose one product or service or another. Things like demand elasticity, brand awareness and drivers of choice at each journey stage are critical. And, of course, you need to understand when and why those choices might favor the competition.
None of this stuff will make a strategic decision for you. It won’t tell you how much to invest in digital. Whether or not to build a mobile app. Whether personalization will provide high returns.
But without fully understanding audience, journey, drivers of decision and competitive choices, how can any digital decision-maker possibly arrive at an informed strategy? They can’t. And, in fact, they don’t. Because for the vast majority of enterprises, none of this information is part-and-parcel of the information environment.
I’ve seen plenty of executive dashboards that are supposed to help people run their businesses. They don’t have any of this stuff. I’ve seen the “four personas” puffery that’s supposed to help decision-makers understand their audiences. I’ve seen how limited is the exposure executives have to journey mapping and how little it is deployed on a day-to-day basis. Worst of all, I’ve seen how absolutely pathetic is the use of voice of customer (online and offline) to help decision-makers understand why customers make the choices they do.
Voice of customer as it exists today is almost exclusively concerned with measuring customer satisfaction. There’s nothing wrong with measuring NPS or satisfaction. But these measures tell you nothing that will help define a strategy. They are at best (and they are often deeply flawed here too) measures of scoreboard — whether or not you are succeeding in a strategy.
I’m sure that people will object that knowing whether or not a strategy is succeeding is important. It is. It’s even a core part of ongoing strategy development. However, when divorced from particular customer journeys, NPS is essentially meaningless and uninterpretable. And while it truly is critical to measure whether or not a strategy is succeeding, it’s even more important to have data to help shape that strategy in the first place.
Executives just don’t get that context from their analytics teams. At best, they get little pieces of it in dribs and drabs. It is never — as it ought to be — the constant ongoing lifeblood of decision-making.
I subtitled this post “The Role of Voice of Customer in Enterprise Analytics” because of all the different types of information that can help make strategic decisions better, VoC is by far the most important. A good VoC program collects information from every channel: online and offline surveys, call-center, site feedback, social media, etc. It provides a continuing, detailed and sliceable view of audience, journey distribution and (partly) success. It’s by far the best way to help decision-makers understand why customers are making the choices they are, whether those choices are evolving, and how those choices are playing out across the competitive set. In short, it answers the majority of the questions that ought to be on the minds of decision-makers crafting a digital strategy.
This is a very different sort of executive dashboard than we typically see. It’s a true customer insights dashboard. It’s also fundamentally different than almost any VoC dashboard we see at any level. The vast majority of VoC reporting doesn’t provide slice-and-dice by audience and use-case — a capability which is absolutely essential to useful VoC reporting. VoC reporting is almost never based on and tied into a journey model so that the customer insights data is immediately reflective of journey stage and actionable arena. And VoC reporting almost never includes a continuous focus on exploring customer decision-making and tying that into the performance of actual initiatives.
What decision-makers mostly get (if they get anything at all) is a high-level, nonsegmented view of audience demographics, an occasional glimpse into high-level decision-factors that is totally divorced from both segment and journey stage, and an overweening focus on a scoreboard metric like NPS.
It’s no wonder, given such thin gruel, that decision-makers aren’t using data for strategic decisions better. If our executives mostly aren’t Dilbertian, they aren’t miracle workers either. They can’t make wine out of information water. If we want analytics to support strategy — and I assume we all do — then building a completely different sort of VoC program is the single best place to start. It isn’t everything. There are other types of data (behavioral, benchmark, econometric, etc.) that can be hugely helpful in shaping digital strategies. But a good VoC program is a huge step forward — a step forward that, if well executed, has the power to immediately transform how the digital enterprise thinks and works.
This article was written by Gary Angel from CIO and was legally licensed through the NewsCred publisher network.