Why Dashboards Fail
When we build dashboards and automate reports, it’s rare to consider a human-centric approach to delivery. As a Data Analyst, this can feel too aspirational. After all, building dashboards, reports, data products, or even data applications aren’t emotionally charged tasks. Or are they? Effective data communication isn’t worthy of empirical study or heuristics so, why should marketers seek to apply it; let alone understand why consumers need it? Connecting the usage of data platform to specific outcomes is vital, building an experience and driving platform adoption matters, so why do we continue to miss the mark?
Here are the startling facts: Conservatively, 80% of all Business Intelligence projects fail to deliver expectations and just because a solution was delivered on time or on budget, it doesn’t necessarily mean it will be adopted or drive measurable value. Customers are left with a bad experience. One that is all too familiar.
As marketers, we understand two types of data: quantitative and qualitative. Quantitative measures give us insights into customer behaviors, e.g., logins, impressions and page views. Analysts most often responsible for building automated reports or dashboards are quite familiar with these measures. That’s the “What”. However, understanding the qualitative side of data product development is less clear. Analysts and Project Managers are responsible for “how” projects are built and when it is delivered but are less focused on “why” a project is needed and who benefits from it. On-time delivery is important, but is only a fraction of the equation. With so many resource constraints, and competing priorities, the business incentive is understandably misaligned. Project management methodologies teach us to document everything, but the “why” of project development can’t be solved by simply gathering business or technical requirements. As a result, we forget to deliver on the promise of customer satisfaction, motivation, loyalty, and usage of the platform. Typically, these are elements that are measured after a project is delivered but are rarely considered at project inception. This can understandably feel alien to traditional data project teams because it requires a different skillset, tools, and understanding – a complete reframing of our north star objectives beyond profit and delivery is required. Our projects continue to fail. And we need data empathy. But where does that line item fit on a gant chart?
“Data-driven empathy is about humanizing data: bringing personal insights to life in a way that allows you to know your customer beyond the incomplete information that populates traditional systems of records. It’s about the intent to seek these insights, aligning systems, operational models, and processes focused on unifying and analyzing customer data so that it’s insightful, actionable, and personal.” Brian Solis [futurist, author, and Global Innovation Evangelist at Salesforce]
For example, Marketers know that the dashboard delivery process begins with data onboarding, preparation, and visualization. But, well before we’ve onboarded a single data row, there’s a key component conspicuously missing from our discovery and build processes. We need to understand the why and how our consumers use dashboards before we can ever successfully deliver one. To achieve data empathy, we need to talk, listen, and learn from customers to find out their perceptions, needs, workflows and objectives. This is achieved by adding customer empathy to our delivery process. Unfortunately, it’s very hard to accomplish, but necessary. In fact, the success of your project depends on it.
Marketing dashboards often showcase goals, conversion rates, and related cost per efficiency metrics, to name a few. But today, we fail to understand how business decisions are actually made using supplied data and for better or worse, there’s a culture absent around how data can or should be socialized. Unfortunately, neither are typically considered in the delivery process and once again, we are in danger of missing our primary objective — build data products that drive adoption and demonstrate value. Marketers responsible for delivering data products need new methods for defining success whether it be driving customer satisfaction, increasing adoption, or raising usage, even before considering traditional performance metrics of marketing effectiveness and efficiency. This is the missing imperative that negatively impacts platform adoption and betrays everything we are trying to accomplish.
Until these primary, behavioral metrics are understood, tracked, socialized, improved, and integrated with our data product delivery process, marketers will never achieve data empathy and the marketing platforms built for our audiences will continue to be unappreciated and undervalued — and that 80% failure rate will remain. Our customers need a better data experience. When will you ever deliver it?
Data empathy is that critical first step. Take it.