Tableau Software : How Kimberly-Clark saved $250k with a platform powered by Tableau, Amazon Redshift, and Panoply

Ask Helena Carre, EMEA Omnichannel Analytics Lead at Kimberly-Clark, about the Tableau platform running on Panoply, and she'll tell you it's like having 'analytic superpowers.'
Carre spends most of her time immersed in data, leading the EMEA Analytics team. Kimberly Clark's e-commerce data stems from 15 different regions, aggregated from disparate sources.

The diverse EMEA region has different SKUS and item descriptions for each retailer. The team also collects and analyzes consumer data from multiple internal sources (including data on sales and marketing spend), external sources (like SimilarWeb and Nielsen), and web applications. Combine those SKUs with siloed data and duplicate data points inherent in their legacy systems that include digital shelf analytics and a web-based platform, and their landscape is quite saturated.

It was mission-critical to find a nimble solution. Carre's team chose to adopt Panopy's AI-driven smart data warehousing solution in conjunction with Tableau. The powerful combination has saved the team over 400 hours in a year, equivalent to nearly a quarter of a million dollars, while enabling secure, automated data access to more professionals within the organization. They now spend less time collecting and wading through data and more time interpreting it. The combined strengths of Tableau and Panoply also gives them a 'playground' where they can adjust datasets for ad-hoc discovery. Carre compares 'a data pro without a sandbox to a painter without a canvas'; and her sandbox is something that wasn't available with existing solutions.

'The one-two punch of using Tableau on Panoply for fast performance was the best possible solution for my team,' says Carre. 'It gave me the things I needed - speed, automation, efficiency, flexibility - without blowing up my budget, increasing my headcount, or adding unneeded complexity. It continues to be a great complement to my existing resources.'

As an added bonus, new capabilities for the team have included being able to easily compare side-by-side the performance by store format (i.e. online, in-store, express format, superstore, etc.). Examples of performance metrics now analyzed include: pricing and promotions, pack size, market share and growth.