We’ve all been there. You’ve got a big presentation coming up and need the data to back up your findings, but you don’t have time to convert vast tables of data into eye-catching visualisations. Or you want to drill down into your KPIs to delve into the details, but the data is already out of date.
While data is undoubtedly a goldmine of insights into the state of your business, unlocking those insights can be time-consuming, complex, and difficult to do at scale.
For clothing retailer PEP, issues like these are resolved more efficiently and cost effectively since using the visual analytics platform, Tableau.
Let’s take a closer look at how PEP empowered its team with fast, efficient access to the latest data around stock management.
PEP is Africa’s biggest and most trusted single brand retailer. It employs 17,000 people, operates around 2,400 retail stores, and sells 760 million products a year. Behind the scenes, it has three distribution centres and 13 transport centres occupying more than 250,000m2 — to put that in perspective, that’s the size of 46 football fields.
Three groups of stakeholders at PEP require insights into rejected stock to handle dead stock management.
The first group affected by dead stock was the finance team. They had to write off rejected stock – which amounts to approximately millions of Rands. The stock takes up essential storage space in distribution centres or requires a third party to store it, resulting in a huge potential loss of revenue.
Next is the quality assurance team — they act as the liaison between the distribution centres and Head Office. They require a consolidated view on the data to manage the rejected stock and be aware of what happened between the two departments, keeping a centralised view of Head Office lodging claims and the distribution centres storing stock.
Finally, the supply chain team needs accurate data to reflect the whereabouts of stock in the distribution centres, which is no joke when you’ve got 250,000m2 of inventory to track, plus storage space.
Step 1: automating time-consuming processes.
Data on rejected stock comes from two database systems — an on-premise Oracle database and a Google cloud environment — and 12 main tables. To get actionable insights that support decision making, it needs to be combined with data from six supplementary tables with information on the product, supplier, location, and retail calendar.
“As you can imagine, putting all that data together was tedious and complex, and it was becoming expensive because we had to involve our team of developers to extract data before we could clean it up and present it,” said Izak Visagie, Systems Analyst at PEP.
The company turned to Tableau to automate these time-consuming manual processes and help unlock actionable insights faster and more effectively, as well as to extract and prepare the data for visualisation and analysis.
“Tableau makes data visualisation painless from start to finish. We didn’t have to do any scripting, coding, or programming to get started. It was just drag and drop to connect to the databases and pull in the right tables,” Visagie explained.
Step 2: creating and sharing workbooks.
When the data was ready for visualisation, Visagie passed it to his colleague Sharon Pather, Information Analyst, who created a workbook on Tableau Server. “Tableau is fairly new to me, and I’m really enjoying the journey so far,” she commented. “You can clearly see the rejected stock and with the help of Tableau it’s much more visually appealing.”
She created a minimum viable product (MVP) solution for users to test and discover their data. She could adapt and change the MVP solution quickly and easily as requirements shifted. They could even test the data integrity of new flows without having to start over. Visagie was particularly impressed with the dashboard’s real-time preview of what the final data output would look like.
Sharing workbooks for wider collaboration and analysis helped the team to realise the value of a data-driven culture and see the potential for other use cases across the business. Users can choose who to share it with and adjust permissions so people only have access to the data they need. “The workbook is very clean and simple. We can give colleagues across departments everything they need to analyse data and find out everything they need to know about rejected stock,” added Visagie.
Using Tableau, PEP has empowered users with self-serve access to the latest data to get better visibility of rejected stock. They can share that data with a wider audience, and the whole process is much faster than ever before. But what impact does that have on the business?
Well, the team handled their own data requirements without having to bring in developers to extract and combine it. Which means the development team is free to focus on other, more exciting things — and our team is empowered to do more.
They also automated the entire process, which means they can get the latest data in 15 minutes instead of three days — a massive time saving. And finally, with better visibility of the stock, the company was able to recoup costs amounting to 30 million Rands in the first eight months of using Tableau.
“The solution has empowered the stakeholders to make smarter decisions based on the latest data,” concluded Pather. “We’re really proud of the value we can add to the business – and this was just our first use case! We can’t wait to roll out Tableau to support more of our business needs.”
To learn how Tableau could empower your team with smarter visual analytics, read more here.