When it comes to building actionable dashboards, there is no one right way to go about it; but we have found several good ways that we want to share.
The first key to an actionable dashboards is understanding that data itself will never solve any problems for you; because data is only singular events and outcomes. You can’t gain insights from data alone.
When you have multiple pieces of data, you can start to understand the relationship between them. This allows you to be more informed on what happened.
The next layer is being able to see the bigger picture of the patterns created with all the intersecting pieces of information. This allows you to have the knowledge of why it happened.
But it’s not until you are able to understand the underlying principles of why it happened that you will be able to form an accurate hypothesis of what will happen in the future…
And once you have that foundation, you need to take action in order to create an outcome you desire.
You can see this process illustrated in this graphic:
The next thing that you need to do is look at the type of metrics that you’re building into your dashboard. Is the data that you’re providing purely descriptive of what happened, or is it prescriptive of solutions?
In order for your dashboards to be actionable, they need to make it easy for users to know what to do next.
Taking that evolution further, building predictive models into your dashboards to transform them into forward facing dashboards will propel you into the realm of prescriptive analytics.
The final thing that you can do to make your dashboards actionable regardless of what department you’re building them for is to make sure that you’re avoiding vanity metrics.
Vanity metrics are metrics that provide information, but that don’t drive any action. The best ways to avoid vanity metrics that we have found are: 1) run through metrics mapping before building dashboards, and 2) make sure that you use leading indicators rather than lagging indicators.
The process of metrics mapping helps you avoid vanity metrics by tying every metric to a specific goal, making each data point much more actionable.
As you can see, you start the process with setting goals. While this may seem like a simple task, we have found that over time, many people struggle greatly with this step.
Then, it’s asking important Business Questions that will help you achieve those goals.
Then, we reverse engineer those Questions into Key Performance Indicators (KPIs).
By this point, most businesses are able to have dozens of KPIs per department, but generally speaking only 20% of your efforts cause 80% of your results…. So it’s necessary to prioritize these KPIs.
The first step to prioritization is ranking the KPIs based on business value. How much impact will this have to the organization if we get the answer? The higher ones get prioritized first.
The second thing that you should do is focus on leading indicators rather than lagging indicators. Leading indicators are the metrics that you have control over, and lagging indicators are the results of those efforts.
For example, Salespeople don’t have direct control over how much they’re going to sell, but they do have control over how many calls they make, and how many follow-up emails they send.
The rule of thumb that we use with leading and lagging indicators is that the further the dashboard is from the person performing the action, the more appropriate lagging indicators are, as they are more likely interested in the results than the legwork required to achieve the result.
Now that we have the general tips out of the way, we’ll cover how to make actionable department-specific dashboards
Executive Teams-
Contrary to the advice that we gave earlier, executive dashboards should generally contain lagging indicators.
The reason for this is that they are not in the weeds. They primarily need to see the results of their employee’s efforts, rather than reports on the efforts themselves.
In order to be truly actionable for executive teams, these dashboards should be well annotated around any outliers within the data; as well as have alerts set up for any major deviations from the norm.
Ecommerce Teams-
Ecommerce teams need a lot of data in order to optimize their performance. Depending on their role, they will probably need data around website engagement metrics, data around the customer journey, product metrics, and customer LTV data.
In order to make dashboards around these metrics actionable though, they will need to be prepared for each specific role.
If someone is in charge of optimizing the AOV for new clients, they’ll need to see the purchase rates for each product, including purchase rate by traffic source, as well as data around checkout drop-off rates, and finally data around upsell and cross-sell take rates.
If someone else is in charge of customer retention, they’ll need data around repurchase rates and timelines, what products work well for cross- and up-sells, as well as data around email and newsletter content and performance.
Of course, all of these issues should be addressed in the metrics mapping stage of your dashboard buildout. If you can understand what data and information each role needs, then you can build dashboards to help them answer those questions and optimize for their role.
Additionally, in order to make dashboards actionable for ecommerce teams, each team member needs to know what metrics they are in charge of, and what the expectations are around that role. They need to understand their expectations and responsibilities around each of their KPIs and also the goals for their role.
Finance Teams-
Generally speaking, finance teams are early data adopters in an organization. Alongside marketing, they generally are the ones who understand and leverage data the most.
The data and metrics that a finance team needs at first glance seem to be most straightforward and easiest to track; but in order to create truly actionable dashboards for finance teams, they need deeper insights into monetary performance from around the company.
Generally, finance teams are looking for numbers around revenue projections, cash flow, and cash flow projections; but getting these numbers is where it gets very interesting.
In order to get accurate cash flow projections, you’ll need to have data around the LTV of your customers, including repurchase timelines. Additionally, they’ll probably want to see the data around customer acquisition costs (CAC) and return on ad spend (ROAS) data so that they can weigh in on marketing budgets and investing.
They’ll also likely be interested in HR data and dashboards around cost per employee, monthly benefits costs, and return on investment (ROI) for each employee.
Additionally, they will need data around margins and cost of goods sold (COGS).
While it may seem like the finance team just needs duplicates of each team’s dashboards, in reality, it serves a very different purpose for them. They need this data in order to weigh in on decisions across the company, and help shape the fiscal policy across the organization. While other departments are looking to use this data to optimize their activities, the finance department uses this data to optimize the organization as a whole.
Marketing Teams-
Marketing teams are probably one of the greediest when it comes to data. It’s not necessarily their fault, since they need information around customers, products, and finances.
The main metrics that marketing teams need revolve around acquiring and retaining customers, as that is their primary role in the company.
The metrics that most inform those duties are: funnel conversion rates including a breakdown by source, conversion rates by product, spend metrics, retention rates, and retention rates by product.
That’s just to get their core function done. In order to truly optimize, they need to have data around COGS and margins so that they can understand their allowable CPA.
They need data around the lifetime value of the customers, so that they can optimize around customers who have the highest LTV.
They need to know what sources and products drive the highest repurchase rates and LTV; as well as data around ROAS and ROAS over time.
All of those metrics are just the back-end metrics as well. There are a multitude of front end metrics that marketing teams should and need to manage in order to optimize their ads and drive qualified potential customers to the site.
In order for dashboards to be actionable for marketing teams, they need to provide them with data that helps them do their jobs more effectively and efficiently. It needs to help them understand the customers and their desires better, so that they can more effectively match a product with a customer.
Product Teams-
Product teams occupy a unique position when it comes to data. While marketing’s job is to find customers that fit the products, the product teams need to create products that better suit the needs of your customers.
In order to create actionable dashboards for product teams, it’s important to focus on the metrics that will help them create better products for your customers.
These metrics include product purchase rates, product repurchase rates, usage rates around different features within the products, and customer feedback data.
As with all of the other departmental dashboards, in order for them to make data actionable, they need to have a plan in place for how to use the data.
If they find that one product has an outsized repurchase rate, then clearly you need to develop plans around making more products like that in different verticals.
If they discover that certain features are going unused in the latest product, then it’s probably not worth including those features in the next product rollout.
Conclusion-
While each department requires specific metrics and data in order to improve on their abilities to do their jobs, there are certain things that transcend departments.
The most important ones that we can focus on are making sure that the data is accurate, and in the right hands, and then that we have a plan for how to use that data to inform decisions and turn it into action.
No matter what department you’re in or building dashboards for, if you can make sure that you’re getting the right data in the right hands with a plan, then your dashboards will be successful.