Adatis used data located in various data silos of varying quality, formats availability to help users gain better insight into production levels.
In the fast paced FMCG / CPG industry, identifying issues in production and quality early is paramount to ensure demand is met and overall growth and financial targets are realised.
Yet, historically, to gain meaningful insights, users had to contend with large volumes of granular data, wrangle multiple spreadsheets and rely on poor quality and often incomplete data to answer even simple (but critical) questions, such as:
• Which production regions are on target?
• What region is consistently underperforming and/or failing to meet quality control targets?
• Can we look to optimise production to maximise capacity resulting in higher, improved production in the same time frames?
• Where is the balance of product power, do we need to look to spread the risk?
What’s the value of these insights? In order to invest in infrastructure, stay ahead of the competition and spot opportunities, solid insight is required to determine how to most effectively spend budget. Key decision makers need accurate, rather than speculative, answers to make sound investments.
Using Power BI, Adatis took multi-source/format, tabular data, and transformed it into dynamic, interactive visualisations that allow users to discover insights, leading to better decisions regarding monitoring, problem-solving and ultimately investment.
Now, users can easily:
• Determine total production YTD, against targets, as well as an indication on progress for the current month by region, product and period.
• See production levels and quality issues across the board potentially identifying issues before they occur.
• Track target variances for both high quality produced goods and those that fall foul of the quality control process
• Make meaningful comparisons of production levels and quality across regions, plants, products and time frames.
. . . as well as many more useful metrics and insights.
Using Power BI, Adatis have transformed several unconnected and low quality data into a strategic asset, empowering users to make informed and confident decisions about the production of their products.