In our last blog, we talked about how businesses use a simple framework – What, Why, How – to solve core business problems like revenue, PnL, inventory, and marketing. This is a daily chore for businesses and not a one time exercise. Today, let’s dig into why the “Why” part can be a real challenge that slows down businesses and keeps analysts busy.
Why finding the “Why” is hard
Now while “What is happening to my core metrics” is the first thing you would look at in the morning and you are an expert of “How can I fix the issues,” figuring out “Why” something is happening can be tough. It’s like peeling an onion — you have to go through layers of information, ask the same questions over and over, and sometimes it feels like you’re going nowhere.
The trouble with data
To really understand why something is going on, you need to look deeper than the surface. While your dashboard gives you a quick overview, they are really springboards to many questions that will get you to the root cause issues that you can act upon. This in-depth exploration requires core skill sets, including:
- Understanding the various metrics that form the bedrock of your business.
- Developing a comprehensive understanding of how metrics interact and influence each other.
- Knowing the dimensions in which metrics should be analyzed — cities, customer groups, product categories, and more.
- Understanding where and how data is stored in the organization’s database schemas.
- Knowledge of SQL to extract data from these databases.
- Analyzing the data across metrics and dimensions to identify root causes.
Addressing the “Why” is a daily commitment, ensuring that businesses optimize revenue and mitigate losses. Yet, this routine exploration hinges on an in-depth understanding of database schemas and SQL, thus relying heavily on analysts.
The same old story
Initially, delving into the “Why” can be an exciting challenge for analysts, as it feels like solving fresh problems every day. But over time, it can get repetitive fairly quickly. So analysts end up spending valuable time manipulating SQL filters to answer similar problems, limiting their capacity to take on more impactful problems.
“It’s like having a superhero whose superpowers are spent on doing daily chores instead of saving the city!” (Read more about the challenges faced by analysts here).
The cost of seeking answers
Whenever businesses spot an anomaly, finding out the “Why” can take hours or even days to get to a root cause. This lag can have huge consequences in terms of potential business loss or possible missed opportunities.
Thing to consider here is: Could we be missing crucial opportunities while we're busy gathering a team of data analysts and conducting cross-disciplinary analyses?
Making the “Why” easier
One of our key learnings as operators as well as speaking with multiple other operators has been: business leaders and analysts have specific mental frameworks for solving problems. When they face a familiar problem, they think back to how they solved it previously and apply the same problem solving framework.
The issue is that these mental frameworks don’t usually become common knowledge for the whole organization. This means that problem solving becomes people driven instead of process driven.
It also makes it hard for new team members to understand how to solve problems in the most optimal way. This wastes time and effort for the whole organization.
Imagine if you could translate these mental frameworks into actionable templates, kind of like a Decision Tree. Think of them like maps. You start with a question, like “Why are orders dropping?” Then you follow the map through different steps until you find the real reason, like “Product availability in Florida is low causing a significant drop in customer conversion.”
This is the first step to making problem-solving easier.
But there’s still a challenge. Your teams (business and analysts) still need to continuously dedicate their valuable time and bandwidth to navigate these Decision Trees to get to root-causes.
Now envision a product that can do this work for you. You just ask what is bothering you and the product gets you the root-causes immediately, using the same set of mental frameworks you have been using in the past.
This would significantly save time, simplify tasks, and facilitate shared learning across the team, regardless of their experience levels.
Abstracting the “Why,” so you can focus on creating impact
GobbleCube is an LLM-based guided analytics platform that can help you productize your business problem-solving frameworks.
Business folks can simply ask their questions in plain English from GobbleCube. GobbleCube will understand the context and parameters of the question, identify the relevant framework to use in this context, and quickly run the analysis to provide the root causes.
It’s like having an AI companion that does the heavy lifting for us.
The result? We receive actionable insights instantly, without getting lost in the details of “Why.”
This paradigm shift isn’t just about speed to decision—it’s also about unlocking analytics teams’ potential to explore new growth avenues instead of being stuck in routine tasks.
If you’re interested in exploring these possibilities, give us a shout. We’d be happy to chat!
