At SunnyD, it was all about asking the right questions of the right data sources in order to reduce costs through effective analytics.
By Shawn Roberts, vice president and CIO, Sunny Delight Beverages Co.
There is unremitting attention around the analytics revolution currently taking place. Data democratization is taking hold, empowering business users to make informed decisions. Yet at the same time, IT teams are struggling to maintain governance and achieve a holistic view of their company’s data.
As organizations work to make sense this data, they’re seeking solutions that enable them to focus more on the value-added analytics, rather than data preparation. At SunnyD, data integration has been a major challenge to solve, as we’ve searched for business intelligence tools well positioned to set the standard for next-generation enterprise data analytics.
Using a sound strategy for selecting and deploying an integrated data analytics approach, we realized $1 million in annual savings. This integrated approach enabled us to cut costs related to production planning, transportation, customer profitability and more. This was made possible by asking the right questions to find a solution that can, in essence, power analysis for our analytics.
After asking smart questions, we chose the Birst platform. Its overall value has been in integrating data and providing governance around previously siloed data sources, while also providing self-service analytics capabilities to both technical and non-technical users. As IT teams look to harness the chaos created by an increasing amount of data, while tearing down silos to better serve their customers, they need to keep the following tenets in mind.
Get top-level executive buy-in for your BI deployment
While it may be an overused cliché in the industry, getting support from top-level executives cannot be overlooked. This means more than just the CEO; it includes business leaders from sales, marketing, operations, finance, IT, accounting and more.
Truly understanding each department’s needs and challenges gives credibility to the project and ensures that it’s a collaborative, seamless process.
Consider the needs of each department
Part of getting this buy-in relies on understanding what each user needs in an analytics solution. Equally important is knowing how well the BI solution played with other existing point products that were already doing their job well.
For example, our current logistics and planning tool excelled at forecasting, and our operations team wanted to make sure that any solution deployed wasn’t going to result in more daily work for the team. At the same time, they wanted to see the big picture across the entire supply chain.
Ensure flexibility that meets end users where they are
We wanted the most flexibility when it came to design and end results. Ultimately, we needed a tool that could deliver exactly what each end user, regardless of their technical background, envisioned. After working with individual departments to understand their unique needs, we quickly realized that this ranged from canned reports to complex, ad hoc data analysis and everything in between.
Sales teams wanted tools that enabled them to slice and dice the data, while also giving them the option to create simple, click-and-view reports for findings they shared with directors or regional managers. Likewise, the finance teams wanted everything in Excel so they could look at all of their data outside of the system.
Data integration is crucial to achieve an end-to-end view
With so many dispersed departments turning to data analytics, we knew we needed a solution that could deliver one version of the truth. The issue that we were trying to solve always came back to data integration. We wanted the ability to pull data from each system and create a data warehouse that would mash the data together and then report on a consolidated view of it.
Prior to deploying Birst, our data was managed externally, outside of our ERP system. So, when we performed analytics around promotions, we couldn’t tie it to business performance metrics such as increased order volume. If there was a 15 percent discount, but a retailer didn’t order anything, we had no way to tie the information to orders in our ERP. We lacked a full, end-to-end view that was in one system.
Everything from marketing to manufacturing, to inventory to transportation, was living in a siloed format and required a lot of manual labor to bring it together. With Birst, we were able to run analytics on promotions, giving us the necessary insight to create new business arrangements with wholesale customers, reduce overtime costs for manufacturing and ship products more effectively around a promotion—all small changes that were informed by data and added up to $1 million in savings.
Our goal was to find a solution that not only provided the flexibility each team needed, but also performed valued-data integration at the core of its architecture. With Birst, we were able to balance data governance challenges with self-service needs at an enterprise scale. As IT teams set out to control the data madness, they must consider a similar strategy to ensure they invest resources in the right place.