Daikin

About Daikin Europe

Daikin Europe N.V. is the European arm of Daikin Industries, the Japanese air conditioning group founded in Osaka in 1924. Established in 1972 and headquartered in Ostend, Belgium, Daikin Europe employs more than 13,700 people across over 57 consolidated subsidiaries.

It runs 14 production sites in Belgium, the Czech Republic, Germany, Italy, Spain, Austria, the UK, Turkey, the UAE and Saudi Arabia. Its portfolio covers heating, cooling, ventilation, air purification and refrigeration for homes, businesses and industry across EMEA.

Its customer engagement centre handles very high inbound volumes from all EMEA markets.

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Challenge

Daikin's customer service and order teams handled a high volume of tickets across spare parts, sales administration and contact service. The work was manual, and nobody had a clear view of where to start improving it.

• Every request was read, categorized and routed by hand.
• Processes differed by region. Without harmonization, automation could not be introduced.
• Existing process-mining tools gave limited visibility, so there was no data-driven view of which processes to change or automate first.
• Manual classification and assignment cost time on every ticket and made it hard to reach the right team or agent.
• Little insight into ticket volumes, trends or the impact of automation.

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Solution

1. See the process. Tekst applied process intelligence to Daikin's live ticket and event data. It mined the real customer-contact processes by country and by process, combined with input from the business. The result was a prioritized, data-driven automation roadmap.

2. Act on it.

• Classification: AI classifies every incoming ticket, so it enters the queue already categorized, with all fields structured.
• Assignment: skill- and capacity-based assignment sends each ticket to the right agent. It was piloted with the ADV teams and then extended to Contact Service.
• Reporting: teams ask for volumes, trends and automation impact in plain language in Microsoft Teams and Copilot, through Tekst's MCP server.

3. Close the loop. The same analysis quantified the next opportunities: order intake (about 30,000 orders a month, around 6 minutes each by hand) and quote automation. Both are sequenced next, into SAP S/4HANA.

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Result & Next Steps

Within weeks of go-live, every ticket at Daikin Europe entered the queue already categorized and assigned. Teams now route, prioritize and report on structured data instead of reading each request first. And the first wave is only the start. Daikin uses Tekst Process Intelligence to find and size what comes next, and has already identified around 30,000 orders a month and 200,000 hours of quote work a year to automate in SAP S/4HANA.

• 2M+ tickets auto-classified
• 1,800 working days of manual handling removed
• 20+ seconds saved per ticket on classification and assignment
• Every ticket created automatically, with all fields structured, ready to route, prioritize and report on
• Automation across multiple teams
• Reporting on demand in Teams and Copilot
• A quantified roadmap

The discovery-to-execution loop now drives an expanding roadmap across EMEA: further assignment waves, order intake and quote automation into SAP S/4HANA.

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