Your Step 1 towards exceptional Business Intelligence (BI)
"A value proposition is not just about features and benefits. It's about how your product or service can solve your customers' problems and make their lives better." - Steve Blank
Quotes like these can be applied to internal customers too. After all, A Business Intelligence dashboard is a product created for a purpose - a foundation for data-informed decision-making (and data-driven decision-making).
You've interacted with Business Intelligence regardless of your industry and role today.
Business Intelligence (BI) serves as the compass guiding businesses toward success. It's not just about collecting and presenting data; it's about enabling informed decisions that fuel growth. Visit the world of BI with me, unravel its significance, and understand how to distinguish an effective BI dashboard.
In this edition, I want to introduce my BI Brilliance Blueprint Framework, a compass I've used over the years to enhance the dashboards I built and to reap all the benefits that I've elaborated on later in this article.
What is Business Intelligence?
Business Intelligence (BI) is the process of gathering, analyzing, and presenting data to assist businesses in making well-informed decisions. It's the key that unlocks the door to data-driven success.
With BI being a foundation for every business, it’s absolutely critical to have access to vital (if not all) information that you need to make decisions today. Every business has some form of BI (manual processes included), but not every BI dashboard is good. I've built my share of poor dashboards. It wasn't until I shifted my mindset from "building what is asked" to "building what is needed" that I became truly effective.
So, What Is a Good BI Dashboard?
You’ll find several varying opinions, and recommendations on which BI tools, which chart to represent what kind of info, and how to optimize the performance of data refresh but all of them are more focused on improving the appearance for the dashboard user and less on the value it adds.
I’ve written about it before and will reiterate it again.
The true worth of data doesn't lie in its storage, access, model accuracy, or presentation; it lies in its ability to drive decisions and fuel business growth.
That is the focus of this edition - the value of a BI dashboard and not cosmetics.
You’ll learn to evaluate any Business Intelligence dashboard with just 2 fundamental questions.
What happened?
Where did it happen?
With advances in data visualization tools, dashboards today can also answer a lot more questions. My favorite is - What if. A scenario builder that can be self-serviced (actually I am going to write about it soon!). However, the 2 questions above are the bare minimum as they’ll generate value for the user.
Question 1: What Happened?
Any BI dashboard should be able to answer this basic question about metrics showing historical trends, and an ability to slice it by some attributes. It should enable you to look back in time to where a metric stood. Answering the title question is the foundation of a BI dashboard.
Here are some examples
What were the sales in Jan 2023?
What was the number of units sold in Q4 2022?
What was the traffic to our website last week?
'What happened' is not the beginning of a question but rather a way to inquire about the past tense. It also marks the first stage of Analytical Maturity, which will be my next topic for publishing.
As a user, you should be able to discern how one or more metrics have been trending recently, whether it's on a daily, weekly, monthly, quarterly, or yearly basis.
Understanding a metric's trend is often a high-level question. In my 14 years of experience in analytics, I've never encountered a situation where a user simply stopped at overall trends. It's as if, in a matter of seconds, minutes, or sometimes a mere two days, the same user wished to dissect the overall metric by various attributes.
Put simply, an attribute is a means of dissecting the metric within the same time frame, whether it's a day, week, month, or year. Let's use your personal expenses as an example. If you spent $7k last month, that's your primary metric. The attribute, in this case, would answer the question of where you spent that $7k. You could break it down into categories like Rent, Utilities, Groceries, Shopping, and so on.
Now, envision a BI dashboard that displays your spending over the past 12 months. It provides you with an overview of your expenditures (the metric), and your curiosity drives you to explore further by examining the composition of your monthly spending.
In the business world, attributes might include demographics, platforms, acquisition channels, or other industry-specific categories. They allow you to slice and dice your metrics to gain a deeper understanding.
So, covering metrics and the ability to drill down by attributes is 101 for a BI dashboard.
Question 2: Where Did It Happen?
When you begin to analyze the historical performance of your business metrics, you'll encounter both spikes and drops. Some metrics are better when they're higher, such as $Sales or %Customer Satisfaction (CSAT), while others are better when they're lower, like $Refund or %Downtime of the website. Regardless of whether a metric spikes or drops, you'll always want to understand the cause.
Does the question 'Why is our revenue dropping month over month?' sound familiar?
While the natural progression post ‘What happened?’ is ‘Why did it happen?’. We often miss a crucial question in between - ‘Where did it happen?’.
If you ever measure the time from the event to finding a root cause, this is where most of the time is spent – on dashboards and reports. When a metric drops (like revenue, for example), you want to understand why it drops. Unless the answer is obvious, such as a deliberate reduction in business in specific regions, your first instinct is to slice the data to determine if the drop is specific to certain attributes or if it's a more widespread issue.
A straightforward question you'll want to answer before proceeding further is whether the revenue drop occurred across all territories or if it was specific to certain areas. Knowing this will guide your investigation in different directions.
A good BI dashboard should assist you in swiftly answering this question: where is the drop? While most dashboards allow you to slice your metrics by attributes, if you find yourself investing a significant amount of time determining where the most substantial changes occurred, it's a clear sign of an opportunity for improvement. This improvement equates to an enhancement in the value delivered by the BI dashboard.
Construct your dashboard to not only display metric trends and enable attribute slicing but also to facilitate the quick quantification of which attribute (or even better, a combination of attributes) contributed to the metric's change.
Which answer would you prefer to provide when a metric drops?
The overall number of visitors dropped by 20% compared to last week, with the top contributors being visitors from our mobile app.
OR
The overall number of visitors dropped by 20% compared to last week, and 60% of the drop is attributed to the mobile app and iOS users.
The first response addresses how much the metric dropped (what happened) and identifies the top contributing attribute (where did it happen). In most cases, this will prompt further inquiry, potentially involving quantification.
The second response also covers the extent of the metric drop (what happened) and specifies which attribute, or combination of attributes, contributed to this 20% change (where did it happen).
The second statement offers the most value in terms of awareness, time saved, and providing a clear direction for further investigation. It offers a strong lead and a precise idea of where to focus your inquiry. In this case, you'd want to investigate the mobile app and iOS specifically since they contribute the most to the drop.
To illustrate this concept in personal spending, imagine your expenses increased by 20% compared to the previous month. It's valuable to know that 60% of that 20% increase is attributed to groceries and Costco. This information provides a clear focus area for your attention.
Benefits
Reduced Time Spent on Dashboard Browsing:
Those dedicated to investigating metric movements understand the true value of time. The sooner you pinpoint where to focus, the quicker your investigation can progress. Time saved can be better utilized in uncovering the "why," often achieved through exploratory analysis. It also provides analysts with more time for in-depth analysis and actionable recommendations.
Self-Service for Everyone:
The power of self-service is immeasurable. When individuals throughout your organization can find answers to their queries independently, productivity soars. A well-designed BI dashboard, addressing the two questions we've discussed, establishes a strong foundation for efficient analytics operations.
Enhanced Decision-Making:
When everyone within the organization can easily access and comprehend data, swiftly identifying factors contributing to spikes or drops, it marks a significant step toward nurturing a culture of data-informed decision-making.
Wrap-up
In a world of data complexity, BI Brilliance Blueprint Framework can be your guiding light, making answers to 'What happened' and 'Where did it happen' crystal clear. This not only streamlines decision-making but also saves you valuable time you'd otherwise spend swimming in data. Plus, it transforms your entire team into data wizards. So, if you want to unlock your business data's full potential, just ensure your BI dashboard can answer these two simple yet powerful questions.
Can you dashboard answer these 2 questions?
Thanks for reading. I’d love to hear your feedback. You can either comment or reach out to me here.
If you stumbled upon this, or it was forwarded or shared with you, please consider subscribing to my FREE newsletter, Framework Garage, and join a world brimming with mind-expanding yet simple frameworks, stimulating ideas, and real-life applications.
