tesa Connects Machine Data, Back-Office Systems and Gen AI Innovations with Snowflake

For consumers, manufacturers and businesses alike, tesa is the first and last name in adhesives. With 7,000 self-adhesive products for industrial customers and around 300 consumer products, tesa is not a company that sits still for long. The adhesive manufacturer is constantly innovating, both in its products and the way it operates. 

tesa’s innovation starts with data. But while the company has plenty of insights to work with, it wanted a new way to extract data from its manufacturing machines and integrate it with back-office systems. The company also wanted to consolidate multiple systems and skill sets across its 5,200 employees.

There were plenty of elements to bring together, so tesa needed a strong adhesive to bring everything together. It found this, and more, in Snowflake’s AI Data Cloud.

Before tesa could begin its journey towards a more innovative, data-driven future, it identified two key areas it needed to address. First, tesa needed a way to extract and analyze vital data from its shopfloor machines. Second, it needed a single platform to unify its data ecosystem and tools, including APIs, IoT Devices and ERP and marketing data.

Most important of all, tesa needed to consolidate its data platform without adding additional skills or complexity to the mix, and without having to build its own platform from scratch.

As tesa continued its data journey, it could see the need for a partner to elevate and accelerate its digitization efforts — while offering capabilities and a mindset that matched tesa’s ambition. As the manufacturer’s Head of Data Management and Analytics, Sanjeev Kumar, puts it: “data and analyzing this data is the basis of our business. Now, we’re looking to take that to the next level with AI. We saw Snowflake was on the same journey as us with its focus on AI.”

Kumar and his team assessed several platforms to find the right fit. But it found that Snowflake was the best match for tesa’s business and its people. “Choosing a platform that fit with tesa was key,” explains Kumar. “That’s something we found with Snowflake. We can give it to anyone in the team and they can start using it straight away. There’s not much change and people management needed. It’s a quick ramp up.”

tesa has put Snowflake’s AI Data Cloud to use across four of its most critical operations.

The adhesive manufacturer uses Snowflake to achieve a 360-degree view of customers, tracking leads from comparison and opportunity through to sales conversations. With Snowflake, tesa staff around the world can use the same unified dashboards to get an end-to-end view of the customer journey.

In the back office, tesa uses the AI Data Cloud to manage customer services across its global operations. By tracking customer requests from different storefronts and channels, tesa teams can conduct in-depth analytics to understand market trends and customer sentiment across different markets.

Across its production facilities, tesa uses Internet of Things sensors to harness machine data and bring those vital insights into Snowflake. By combining this with production model data, tesa’s plant teams can identify trends in machine performance and material usage to optimize plant processes. In the future, tesa wants to improve anomaly detection across its sites by using machine learning.

The final and most innovative use case involves using Snowflake Cortex AI to bring the power of generative AI to tesa. “We’re looking at using generative AI to help our people write SQL in minutes and compile it faster than ever before,” says Kumar. “There are so many potential use cases here. And there are a lot more ideas and scenarios on our agenda.”

tesa has covered a huge amount of ground with Snowflake already, within just two years. “The time to market has been very fast,” says Kumar. For example, tesa ran a proof of concept using large language models to automatically segment customer complaints so teams could better understand customer sentiment, identify any product issues and respond faster. Using Snowflake Cortex AI, tesa was able to get this PoC up and running in just a single week. And for its plant operations use cases, tesa can onboard any plant within a week. 

The cornerstone of tesa’s rapid deployment is Snowflake Copilot. With Copilot, tesa can accelerate SQL development and identify potential issues across its data platform by making queries in natural language.

In a short span of time, tesa has transformed its innovation pipeline — integrating machine data, back-office insights and other processes. “Innovation and speed have been the big wins with Snowflake,” says Kumar. “I’ve spoken with consultancy partners in the past who suggested it would take weeks to get machine data from plant systems like ours. We can do it in a matter of hours with Snowflake.”

The AI Data Cloud saves valuable time as well. With more data at their fingertips, tesa’s service teams can trace customer service calls back to specific products in mere hours, avoiding further issues or wastage while continuing to maintain the high quality standards of tesa’s adhesive products.

Snowflake and tesa’s collaboration is already delivering value across the adhesive manufacturer’s back-office, plant floor and customer-facing channels. But the two organizations are just getting started.

tesa plans to continue expanding its plant floor data initiatives, and is looking to offer even more self-service tools so plant managers can query their own data without adding to the backlog of tesa’s central data science team. 

As part of its Gen AI rollout, tesa plans to build virtual assistants that can help sales reps answer complex questions about its industrial adhesive products even faster. 

These transformative use cases only scratch the surface of tesa’s data and AI ambitions. “Now we have a proven template for managing plant and sales data, our next step is building out our data science and large language model capabilities,” says Kumar. “ Not just on documents, but also using Gen AI through Snowflake Cortex Analysis to query our data in new and valuable ways.”

“The relationship with Snowflake has been really good,” says Kumar. “We get support, customized products and direct access to engineers when we need help with more complex use cases, and that’s helped us take a big step forward.”