Platform Analytics: Success Starts With the Business Question, Not the Dashboard

Donta · an hour ago

Many reporting projects begin with a request like, “We need a dashboard.” However, successful analytics initiatives start with a very different questions: What business decision are we trying to make? In my experience working with customers on reporting and analytics requirements, the most effective dashboards are not built by starting with charts and visualizations. They are built by first understanding the business problem, defining the KPI, identifying the data, and determining who will consume the information. The dashboard is simply the finished project. I like to use the cake analogy when explaining Platform Analytics to my customers.

Imagine walking into a bakery and saying:

I need a cake

The baker’s first question shouldn’t be:

What color frosting do you want?

Instead, they need to understand:

What type of cake are you making?
Who is the cake for?
How many people will it serve?
What ingredients are required?

But before designing a dashboard, we should first understand:

What questions need to be answered?
What metric will measure success?
Where does the data come from?
Who needs the information?

Example Dashboard Request:

"Can I get a dashboard showing asset information?"
That sounds reasonable on the surface, but it doesn't tell us what problem we're trying to solve.

A better question might be:

Which assets are due for refresh?
Are we meeting fulfillment targets?
Which departments have the highest exception rates?
Are compliance metrics trending in the right direction?

Step 1: Define the Business Question

Examples:

Asset Management

Which devices are approaching end of life?

Service Catalog

Which catalog items generate the highest request volume?

Fulfillment

Are hardware requests being fulfilled within established targets?

Compliance

Which organizations have the highest policy violation rates?

Notice that these questions focus on business outcomes rather than visualizations. When gathering requirements, spend time understanding the decision stakeholders are trying to make.

A useful question I often ask is:

"If I gave you this dashboard tomorrow, what action would you take based on the information?"
If nobody can answer that question, the requirement probably needs additional refinement.

Step 2: Define the KPI

Once the business question is clear, the next step is defining the Key Performance Indicator (KPI).
The KPI measures success.

Examples:

Business Question	KPI
Which assets need refresh?	Number of refresh eligible assets
Are requests fulfilled on time?	Fulfillment SLA achievement rate
Are we compliant?	Compliance percentage
Are requests increasing?	Request volume trend

Step 3: Identify the Data

Questions to ask:

Which table contains the data?
Is the data complete?
Is the data accurate?
Do we need historical trending?
Are there any gaps in the process that impact reporting?

Lesson Learned

One of the most important lessons I've learned is that a well-designed dashboard cannot compensate for missing or poor-quality data. Before building analytics, validate the data foundation.

Step 4: Understand the Audience

Executives Typically want:

KPIs
Trends
High-level summaries

Managers Typically want:

Operational visibility
Team performance metrics
Areas requiring attention

Analysts Typically want:

Detailed records
Drill-down capabilities
Root cause analysis

A Simple Framework Before creating a dashboard, ask these five questions:

What business decision are we trying to make?
What KPI measures success?
Where does the data come from?
Is the data trustworthy?
Who is the audience?

Conclusion

Successful Platform Analytics implementations do not begin with dashboards. They begin with business outcomes.

Remember the cake analogy:

The business question is the recipe.
The KPI is the ingredient list.
The data is the raw material.
The audience determines how the cake is decorated.
The dashboard is the finished product.