Abraca-data: what data would you wish for?

We asked demand planners: If you could have a magic wand and get any type of data to improve your KPIs – what data would you want?

We asked demand planners: If you could have a magic wand and get any type of data to improve your KPIs – what data would you want?

In our latest whitepaper, our experts asked this question in interviews with 80+ supply chain and demand planning professionals. Through this question alone, we gained enough insights to determine areas in the field lacking information that decision-makers want.

With the responses received, we identified 10 themes. These themes include: Internal Data for Reporting, Trend Data, Competitors Data, and many more. According to the professionals we spoke with, this data would answer pressing questions. The questions that could be answered by more – or better – data ranged from more challenging issues like “How can I reduce the hours wasted on manipulating data?”, to simpler ones like “What are competitors selling?” or “How are those products performing?”.

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You can learn more about the gaps in data and the impact its having on professionals in our whitepaper, available for free download here.

How do you get started in making new data accessible for demand forecasting?

Incorporating new data into demand forecasting can improve the accuracy of predictions and help businesses make informed decisions. Here are some steps to incorporate new data into demand forecasting:

  1. Infrastructure: Make sure you have the tools, software, and technology required to manage and process the additional data. This involves having adequate processing speed, storage capacity, and data management tools.
  2. Assess integration points: Assess how the new data will fit into your current demand forecasting system. Think about the procedures for gathering, analyzing, and incorporating the data into your models.
  3. BI: You can evaluate and display the new data with the use of business intelligence (BI) tools, gaining insights that could boost the accuracy of your demand forecasting.

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