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Automation

TECH FLASH

10 steps to making analytics pay in manufacturing

Plant floor analytics have to be linked with customer-focused processes to be the most beneficial.

By Shane O'Halloran
October 29, 2013

10 steps to making analytics pay in manufacturing

Successful manufacturers know building out their records of plant floor performance can pay significant dividends based on the intelligence they can provide. Plant floor analytics are fundamental to improving plant, manufacturing, financial and enterprise-level performance, but the linkages between analytics and intelligence can be easily missed. Louis Columbus of Plex Systems offers 10 strategies for “making analytics pay,” with the goal of unifying diverse manufacturing lines and programs with a common strategic direction:

 

1. Establish a baseline by measuring existing manufacturing systems and process performances. A baseline can be established easily through common metrics or analytics.

2. Identify the three manufacturing processes with the greatest impact on customer interactions and create metrics to measure their performance from a consumer’s perspective. Adding perfect order performance and other customer-centric measures can help avoid the inside-out mindset that dominates many manufacturers’ use of analytics, says Columbus.

3. Value stream mapping, or a similar technique, can help make immediate cost and time differences. For some manufacturers, that could mean moving from master production scheduling to same-day, closed-loop scheduling or relying on sales and operations departments to plan production together.

4. Design customer-centric metrics for the processes in step two and include them in a dashboard. A dashboard including customer-focused metrics like product quality, on-time delivery and perfect order performance links production floor performance to financial results. These metrics will form the basis for three pilot programs to strengthen linkages between analytics and business performance.

5. Give each pilot program leader the ownership of his or her program for best results. Allowing the people most affected by potential changes to have a sense of ownership takes trust—but also creates it.

6. Create metrics of performance that illustrate and reward collaboration for each pilot program, both inside the company and across suppliers. As Columbus says, “One of the most valuable aspects of analytics is their inherent power to provide recognition and reward collaboration.” He recommends using forecasting performance as a measure of combined team performance.

7. Evaluate the performance of each customer-driven manufacturing process and choose one to implement company-wide. Manufacturers can use analytics to benchmark the performance of each process, showing them how to improve from the customer’s standpoint. The customer-facing manufacturing process with the greatest potential benefit often becomes clear through analysis.

8. To get the company behind the use of analytics to drive greater performance, use data evidence from the pilot programs. Columbus describes a CEO who launched three pilot programs in an effort to better integrate his company’s CRM system into manufacturing. That CEO was able to attain record adoption of the new analytics after showing how helpful they could be.

9. According to Columbus, “Engraining a customer performance-driven mindset begins with stable, accurate analytics that tie plant floor performance to financial results via the customer.” Doing so can help teams work together and focus on making their collective performance better because it is so visible.

10. Analytics for measuring performance need to keep up with changes in your customers’ businesses. Staying consistent with customers’ needs and requirements is a must.

 

Extending analytics past the shop floor allows manufacturers to create an agile business by galvanizing manufacturing systems, strategies and processes. For more on making the most of analytics, check out the Plex blog.

KEYWORDS: data acquisition manufacturing intelligence

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