Excel in Bi

There is no doubt there are multiple ways to approach a business problem, with the understanding of the current situation and interviewing who is involved to create a possible solution or bring background information to create the business problem context.

This is the case if we would like to analyse that a Company’s Growth has decelerated in the last 2 years. One approach is to talk with the sales team and try to understand why the Company is growing, or in this case, the sales have stopped increasing in the last 2 periods. Their answer can be related to factors like:

• Our stock availability has been positioned as the competitor with the worst delivery time.
• We do not have enough Sales Agents to visit customers.
• We have stopped our presence in roadshows.

If we would like to take these reasons with more interest and defend them on the director’s board, we will require vital data that will create trust in our requirements.

The 5 techniques that helped in the past and keep providing me value to analyse this Business problem are:

1. Listen:

• This is a crucial step. Listening to stakeholders and understanding their concerns and objectives sets the foundation for effective data analysis. Active listening to your stakeholders is crucial to tackling the situation. Without proper listening at the beginning of the process could result in going back and forward across multiple teams to keep trying to understand the problem. Just remember to keep each point of view a part of the puzzle to resolve the problem.
• Listening can be a dynamic and interactive process that can include techniques such as conducting interviews, surveys, or focus groups.

2. Analyse the pain:

• Understanding the pain points or challenges faced by the business is essential for targeting data analysis efforts effectively. Creating a space where the teams can express their concerns about the situation can create a collaborative environment to untamed the business problem. The Sales Department could complain about the logistics not having the stock available on time, on the other hand, The Logistics Department could complain about finance not making the funds available to increase the stock values.
• All these situations and examples will require to be later analysed with the data related, for example, the product stock volume and the number of sales orders by item, together with the payment policies from the Financial team.
• This analysis will help you to prioritize which analysis requires to be made first, using techniques such as SWOT analysis can help you further (Strengths, Weaknesses, Opportunities and Threats).

3. Find which data is available:

• Assessing the available data sources is critical for determining the feasibility and scope of the analysis.
• Guide how to evaluate data quality, accessibility, and relevance to the problem at hand. Discuss techniques for data collection, integration, and preprocessing if necessary.

4. How will be the audience:

• Considering the audience is key for tailoring the analysis approach and communicating findings effectively.
• Elaborate on the importance of understanding the audience’s level of data literacy, their preferences for data presentation, and their specific informational needs.

5. Provide different Analyses for the Business Problem with the data as the main backup to prove the point and the elaboration of the stories around them.

Data + Storytelling = Success.

In addressing a business problem like decelerated growth, it’s crucial to not only identify the underlying causes but also present compelling evidence to support potential solutions. This involves leveraging data as the primary tool to substantiate hypotheses and craft persuasive narratives.

Effective data analysis isn’t just about crunching numbers; it’s about telling a story that resonates with stakeholders and drives action. By combining data-driven insights with compelling narratives, you can create a compelling case for change.

Hands-on work to resolve this problem within these 5 Techniques.

Start by conducting thorough analyses of the data relevant to the identified pain points. For instance, if the sales team cites stock availability as a major issue, delve into inventory data to understand trends in stock levels, order fulfilment rates, and customer satisfaction metrics. Similarly, explore sales agent performance metrics, customer engagement data, and marketing campaign effectiveness to uncover insights into potential staffing and customer engagement strategies.

Once you’ve gathered and analyzed the necessary data, it’s time to craft narratives that bring the numbers to life. This involves translating complex data findings into compelling stories that resonate with your audience. Use visualizations, anecdotes, and real-world examples to illustrate key insights and underscore the urgency of action.

Furthermore, providing multiple analyses allows for a comprehensive exploration of potential solutions. Consider employing techniques such as predictive modelling to forecast future trends, scenario analysis to evaluate different strategic options, or prescriptive analytics to recommend specific courses of action. Each analysis offers unique insights into the problem at hand, empowering stakeholders to make informed decisions.

Remember, the ultimate goal is to present solutions that are not only backed by data but also communicated in a clear, concise, and compelling manner. Whether through presentations, reports, or interactive dashboards, ensure that your findings are accessible and actionable for your audience.

In summary, combining data-driven insights with compelling storytelling is the key to effectively analyzing business problems and driving meaningful change. By providing multiple analyses supported by robust data, you can inspire confidence in your recommendations and empower stakeholders to take decisive action.

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