Intelligent CIO APAC Issue 32 | Page 63

CASE STUDY end ,” said Jamarl Scase , Planning and Production Control Manager at Camatic Seating .
Improving sales forecasting and customer satisfaction
Taking advantage of the modern Infor OS technology platform that underpins Camatic Seating ’ s Enterprise Resource Planning ( ERP ) system – Infor CloudSuite Industrial Enterprise – Camatic Seating applied Infor Coleman AI to five years of disparate customer relationship management ( CRM ) data to help generate more accurate forecasts and win predictions . Implemented in less than 30 days , the AI-driven insights are delivered through Infor Birst analytic dashboards and insights are accessible on demand .
Before leveraging Infor OS to better utilize data to generate insights , creating monthly sales forecasts was a manual process . Capacity planning , based on these forecasts , was prone to risk and unforeseen costs , such as lack of supplies and outsourcing work to subcontractors .
Now , the entire organization uses the same realtime information to help deliver seating solutions to customers on time . Management and sales teams are more effective in strategic decision-making ; operations are better equipped to plan for capacity and procurement can acquire the right number of raw materials at the right time .
Automating the vendor selection process With Infor Coleman AI applied to vendor performance data , Camatic Seating can automatically assign

WE NOW HAVE THE

CONFIDENCE TO TELL OUR CUSTOMERS WE CAN DELIVER SEATING ON TIME .

grades to suppliers in five categories . Planners can quickly look at multiple suppliers in the same category and compare their ratings . There also is a summary breakdown of past vendor performance – in terms of delivery promptness , quality and price . The Camatic Seating team can select based on the overall ranking and it also can see the details behind the ranking .
“ We weren ’ t analyzing the data consistently and it led to us making incorrect supply selections sometimes ,” added Scase . “ Previously , it was arduous for the material planners to get that data out and analyze it , sometimes taking up to 30 minutes to figure out what the supplier ’ s performance had been . Now , by applying AI to our historical data , they can have that information with more accuracy and consistency at the touch of a button .”
According to Scase , more accurate and targeted vendor selection ultimately leads to better delivery performance and the ability to manufacture betterquality products at a lower cost . p
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