“In God we trust. All others must bring data.”
Statistician and Management Scientist W. Edwards Deming said it best.
Gone are the days of making arbitrary business decisions or using data as “evidence” to support calls already made to make ourselves feel better.
The future of business is data-driven. And that is a very good thing.
You need analytics that present your targets clearly and let you know at a glance whether you’re on track or if you need to support a decision to reroute. Plus, gut feelings aren’t always correct, and figuring out your hunches are off is the first step to discovery.
But how do you translate abstract business goals into measurable data?
With KPIs, of course!
Gartner defines a Key Performance Indicator as:
…a high-level measure of system output, traffic or other usage, simplified for gathering and review on a weekly, monthly or quarterly basis. Typical examples are bandwidth availability, transactions per second and calls per user. KPIs are often combined with cost measures (e.g., cost per transaction or cost per user) to build key system operating metrics.
Just as your business needs clear direction, so does your data. Key performance indicators give you and your BI the guidance needed to make the best possible data-driven decisions.
Great BI tools are completely designed around your KPIs and can offer up relevant data insights in easily digested dashboard visualizations.
But with so many objectives, how do you carve out your KPIs? What’s the difference between KPIs vs. metrics? Exactly where do you draw your lines? Here’s how it all breaks down.
The KPI Hierarchy
There are four tiers of the KPI hierarchy. Each of these should be laid out from the very beginning of your BI implementation workflow, in the planning phase.
1. Business Goal
A general strategy statement that describes a long-term end result attributed to the entire group or organization.
Example: The business goal for the HR department is to improve employee retention.
2. Business Objective
Breaks down the goal into specific, short-term actions that are more tangible and can be measured.
Example: Increase employee retention from an average of X years to an average of Y years.
Measurable indicators that define the expected end result in terms of specific targets, such as number and/or date.
Example: Number of employees enrolled in career development program.
Support the above by indicating the smaller steps and outcomes on the way to achieving the main goal.
Example: Number of career development promotions sent from HR to employees.
- Increase marketing department efficiency.
- Improve conversion rate.
- Optimize cost per lead.
- Amount ofleads.
- Line Items promotion.
- Lead score.
- Advertising costs.
- Amount of leads.
- Number of leads.
- Promotion per line item.
- Costs per lead.
- Number of line items promoted.
- Amount of money invested in promotion.
Still confused about just what the heck qualifies as a KPI?
Ask yourself the morning question. You know. That question your CEO or supervisor asks you right when you come in. It usually sounds something like, “How are we doing with blank?”
For finance, it could be ARR and for marketing, it could be your conversion rate. Whatever is your most valuable measure, the one everyone in the organization wants to know about, that’s your KPI.
(Want a little more on this topic? Check out this must-read on how to define KPIs in four easy steps.)
How to Build Your BI Around Your KPIs
First, outline your goals and objectives. Then, you and your teams gather all the requirements needed to determine exactly what to measure in order to get the most relevant insights from all your data.
Don’t feel limited by disparate data sources. A great BI solution can access any and all of your data, wherever it is and even have built-in data connectors.
The next step is to create a high-level design of your BI solution based on the most meaningful KPIs you and your teams selected.
Your BI system will link your overarching business goals down to the relevant operational data, the detailed row data that helps you understand where your core measures are coming from, so you can see exactly how your KPIs relate to your business goals.
How Can You Make KPIs Easy to Visualize?
Once you’ve nailed down your KPIs, you can translate them into widgets to appear in your dashboard.
Start by associating each of your KPIs to the relevant data source. This can be the source itself and can go all the way down to the relevant tables and fields.
Then, each KPI is broken down into a formula used to calculate that measure. That formula is associated with the relevant table to pull data from, for example, your CRM, financial database, etc. The same process is done for the supporting measures.
So, for example, if your main KPI is conversion rate, you would associate the supporting measure, let’s say, the number of leads, to the relevant table in your CRM.
Your formula will calculate all the leads who made the first order from the total count of leads and present the percentage to you in a user-friendly widget on your marketing dashboard.
Creating Your Dashboard
After you tell your BI exactly how to calculate your KPIs, then it’s just a matter of deciding how you want to visualize your data.
Start by jotting down a mock up — your mock up with a reflection of the hierarchy you outlined, with the most important KPI on top. The top KPI is an indicator that can be represented by numbers or a gauge display in your dashboard.
You define the minimum and maximum range and you can even add colors to your gauge, for example, traffic light colors with red indicating conversion rates in the lower one-third, and green for your marketing efforts are paying off. You can see 10 most useful data visualizations and read about when each one should be used.
The mockup happens well before you create your dashboards and Elasticubes to ensure all your data is modeled correctly, according to the specific divisions and filters your users need.
Your supporting measures are then broken down in separate graphics, for example, cost per lead represented in currency.
How Detailed Can You Get?
Once the supporting measures are in the dashboard, you can start to play with the other data questions your business stakeholders might have, for example, the behavior of your conversion rate over time might be represented by a line chart broken down by years, quarters, and months.
You can also represent the lead sources that contribute to the conversion rate in a bar chart representing the conversion rate with sources name.
In a nutshell, your dashboard can represent your entire main KPI and supporting measures. You can add any and all relevant indicators and operational data factors related to the KPI and its supporting measures.
A word of warning: Once you’ve determined the main objective of your dashboard, you want to make sure you stick to that and avoid diluting it with adjacent data. We recommend sticking with seven to nine relevant widgets max.
So, is your business headed in the right direction? Measuring your KPIs is the only way to know for sure.