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How can you ensure your BI solution predicts demand accurately?

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Business intelligence (BI) solutions can help you analyze data, identify trends, and forecast demand for your products or services. However, to ensure your BI solution predicts demand accurately, you need to follow some best practices and avoid some common pitfalls. In this article, we will discuss six tips to improve your BI demand forecasting.

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Surya Teja

Demand Planner - L'Oréal Paris | IIM Kozhikode'21 | Thorogood Associates | Writer

1 Choose the right data sources

The quality and relevance of your data sources are crucial for your BI solution to produce accurate demand predictions. You should select data sources that are reliable, timely, and consistent, and that capture the factors that influence your demand, such as seasonality, customer behavior, market conditions, and competitors. You should also avoid data sources that are outdated, incomplete, or biased, as they can lead to inaccurate or misleading results.

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Surya Teja

Demand Planner - L'Oréal Paris | IIM Kozhikode'21 | Thorogood Associates | Writer
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When it comes to demand predictions, it becomes important to understand relevancy of data sources rather than just adding data sources. Each model can be refined by adding a new data source but the cost of acquiring data should have a positive ROI. After all, demand prediction accuracy can only take you so far. Rest of the chain's agility is also important to be taken into consideration.

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2 Define clear objectives and metrics

Before you start using your BI solution to forecast demand, you should define your objectives and metrics. What are you trying to achieve with your demand forecasting? How will you measure your performance and success? How will you communicate your results and recommendations to your stakeholders? By setting clear objectives and metrics, you can align your BI solution with your business goals and expectations, and ensure that your demand forecasting is relevant, actionable, and meaningful.

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Surya Teja

Demand Planner - L'Oréal Paris | IIM Kozhikode'21 | Thorogood Associates | Writer
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Demand Prediction accuracy can only lead to certain outcomes if viewed in silo. It is important to evaluate and see the possibilities of the rest of the chain's contribution as well. Accuracy is a post-fact measure and there are too many variables that are not at all taken into consideration while creating the metrics. Hence, it becomes important to understand the efficiency of the chain before investing in demand forecasting accuracy.

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3 Select the appropriate methods and tools

There are many methods and tools available for BI demand forecasting, such as regression analysis, time series analysis, machine learning, and simulation. However, not all of them are suitable for every scenario or data set. You should select the methods and tools that best fit your data characteristics, objectives, and metrics, and that can handle the complexity and uncertainty of your demand patterns. You should also test and compare different methods and tools to find the optimal ones for your BI solution.

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4 Validate and refine your models

Once you have selected your methods and tools, you should validate and refine your models to ensure they are accurate and robust. You should use techniques such as cross-validation, backtesting, and sensitivity analysis to check how well your models fit your data, how they perform on new or unseen data, and how they respond to changes in parameters or assumptions. You should also monitor and update your models regularly to account for new data, feedback, or market dynamics.

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5 Visualize and communicate your results

To make your BI demand forecasting effective and impactful, you need to visualize and communicate your results in a clear and compelling way. You should use charts, graphs, dashboards, and reports to present your demand predictions, along with the confidence intervals, error margins, and scenarios. You should also explain the logic, assumptions, and limitations of your models, and how they relate to your objectives and metrics. By visualizing and communicating your results, you can enhance your understanding, credibility, and decision-making.

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Surya Teja

Demand Planner - L'Oréal Paris | IIM Kozhikode'21 | Thorogood Associates | Writer
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The way to visualize is heavily dependent on the current visualization, and meeting structures of the organization. Some organizations require numbers to focus while some can deep dive with trend graphs. Understanding where the visualizations are being used is the key to understanding the design, logic, and requirement. Needless to say, the design should be easy to understand, scale, and communicate among the relevant groups. Fancier graphs can lose out of messaging while focusing on graphics. Hence, it is important to do testing and get feedback on the visualizations created.

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6 Learn from your outcomes and feedback

The final tip to improve your BI demand forecasting is to learn from your outcomes and feedback. You should track and measure your actual demand against your predicted demand, and analyze the gaps and errors. You should also collect and incorporate feedback from your customers, partners, and stakeholders, and identify the areas of improvement or innovation. By learning from your outcomes and feedback, you can refine your BI solution and make it more accurate, reliable, and valuable.

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Surya Teja

Demand Planner - L'Oréal Paris | IIM Kozhikode'21 | Thorogood Associates | Writer
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Demand Prediction doesn't have a one-size fits all. With products coming in, and going out, you'll need more fine tuning across various parameters. Accuracy, and Bias metrics are numerous and they can help create a tracking signal where focus is needed.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How can you ensure your BI solution predicts demand accurately?

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3

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5

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1 Choose the right data sources

2 Define clear objectives and metrics

3 Select the appropriate methods and tools

4 Validate and refine your models

5 Visualize and communicate your results

6 Learn from your outcomes and feedback

7 Here’s what else to consider

Information Systems

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How can you ensure your BI solution predicts demand accurately?

1

2

3

4

5

6

7

1 Choose the right data sources

2 Define clear objectives and metrics

3 Select the appropriate methods and tools

4 Validate and refine your models

5 Visualize and communicate your results

6 Learn from your outcomes and feedback

7 Here’s what else to consider

Information Systems

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