10 questions i always ask as an analyst for a successful outcome.

What needs to be done? Why? Action-driven or data-driven? So many areas to focus on while getting the analysis right. What guides a successful completion of an analysis. let’s find out!!!

In my previous post, i documented my learnings as a business analyst. I have done numerous projects that have helped me learn the skills of effectively understanding the data, managing the stakeholders expectations, creating a compelling story and delivering an outcome focused on driving actions.

And the data comes with bias, many biases. Learn more here.

But what has helps me get through?

This time, i want to leave you all with a template on how i build my framework.

1. Goal: We’re figuring out what we want to achieve and why it’s important.

2. Audience: We’re identifying who will benefit and use this information.

3. Expected Results: We’re looking at what we hope to find out from this analysis.

4. Known Parameters: We’re considering what could happen if we do nothing and what we assume about the situation.

5. Success Factors: We’re deciding how we’ll know if we’ve succeeded.

6. Optimization: We’re planning how to handle challenges and new information.

7. Output Interpretation: We’re learning how to understand the results correctly.

8. Findings: We’re looking at the key things we’ve discovered.

9. Communications: We’re figuring out the best way to share our findings with different people.

10. Next Steps: We’re planning what to do next based on what we’ve learned.

But what are the questions relevant to these 10 areas of exploration.

Fortunately, i learned something incredibly valuable very early on in my career. That is, people hate to asked “WHY”?

Wait, what? Isn’t the the practice of asking the “5 Whys” is extremally potent in getting to the real motivation. Well, may be? Though not so much in my experience. People just don’t want to be questioned.

But, hang on.

They do love to solve. They really get engaged when they see themselves as a problem-solver? And, people want to collaborate and build together.

So try to stay way from the whys? Give it a try, and see for yourself!!!

So, why are we doing this 🙈😏

1. Goal. What are we trying to achieve with this exercise? What decisions would it drive or help accelerate? Or, what makes this important?
2. Audience. Who gets benefitted from this? Who would use this for easy decision-making? Or, who are my stakeholders & consumers?
3. Expected Results. What are the results that we are hoping to get? What is the scope of the analysis— exploratory, diagnostic, descriptive, predictive, prescriptive? Or, what type of analytical method is applicable?
4. Known Parameters. What happens or is happening if we don’t take any actions? What are we assuming about the question, underlying biases or challenges with the data, the timeline of action, and the expected result? Or, what is the current state and required urgency of required action?
5. Success Factors. What critical factors signify success? What is the baseline of key metrics that will signify a positive lift? Or, what does success looks like and how would it get validated?
6. Optimization. What plans do we have addressing constraints and limitations? How would we incorporate new information as it would appear? Or, how would we mitigate challenges and evaluate trade-offs?
7. Output Interpretation. How to read and understand the results in the context of specific questions, and expectations? How to ensure that interpretations are accurate and not skewed by biases or incorrect assumptions? Or, how do the results align with or differ from our initial hypotheses?
8. Findings. What specific patterns, trends, or anomalies have been identified? Do these findings impact our understanding of the initial problem? Or, in what ways do these findings challenge or confirm our pre-existing notions in a manner that elicits a decision or action?
9. Communications. What findings are needed to be shared with different audience ensuring clarity and relevance to each group? What format and channels will be most effective for conveying this information? Or, what level of details are required to ensure that the communication is persuasive and drives the desired action or understanding?
10. Next Steps. How to implement the recommendations or insights derived from the analysis? What resources or changes are required to execute these next steps? Or, what further investigations or follow-up actions are warranted?

While an analysis is never complete, and there’s no way to produce a perfect outcome in a real world, this framework gives a good outline to cover the major pieces of the exercise.

However, as an analyst you need to be mindful of a few things. Check them out here.

Learn more on the nuances of data and storytelling.

• The fine nuances of data storytelling.
• Challenges faced by every data person.
• The 8 stages of an analysis lifecycle that drives results.
• 10 ways to make your data tell a compelling story.
• 5 ways to make an impact with your analysis.
• 3 most common types of data analysis
• What 15 years of business analysis taught me?