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<\/p>\n\nThis article reflects perspectives built during 4 years at BCG working on LEAN programs, operational performance and cost reduction missions across Europe, Asia and the Americas.<\/em>\n<\/div>\n<\/div>\n
The enterprise MES decision pattern before lightweight OEE existed<\/h2>\n
For the two decades before lightweight OEE emerged as a category, the enterprise MES decision followed a predictable path. A large manufacturer commissioned an RFP, invited three to five tier-one MES vendors, ran a six-month evaluation, selected one, and committed to an 18-to-36-month deployment. The evaluation criteria emphasized functional completeness, vendor financial stability, integration capability, and global support footprint. The small, specialized vendors \u2014 the ones that might have been better fits for specific use cases \u2014 usually could not clear the procurement filter because they lacked scale or geographic coverage.<\/p>\n
The MES that won this RFP process was architecturally overbuilt for most of the clients’ use cases. A Stellantis plant running automotive stampings does not need the same traceability depth as a pharma plant running injectable fills. A Kraft Heinz pasta line does not need the same quality batch management as an aerospace fastener line. But the RFP process asked which vendor could theoretically handle all possible use cases, not which vendor was optimal for the specific plant. The overbuilt MES won, got deployed, and delivered a fraction of the OEE improvement that the original diagnostic had projected.<\/p>\n
What changed when the enterprise clients started evaluating lightweight OEE<\/h2>\n
The inflection point at several of our enterprise clients came when an operations team \u2014 often prompted by a consulting engagement with BCG, Sia Partners, or a peer firm \u2014 asked a specific question: “We already have MES on our critical lines. Why is our OEE measurement on the non-critical lines still based on Excel and shift logs?”<\/em><\/p>\n This question reveals the gap. The enterprise MES covers 20-30% of a multinational’s production lines \u2014 the lines that justify the traceability and compliance investment. The remaining 70-80% of production lines, which may represent the majority of the company’s production volume, are measured with paper and spreadsheets. The OEE performance of these lines is inferred from ERP output data, not measured. The improvement loop on these lines is broken because the data does not support it.<\/p>\n Lightweight OEE solves this specific gap. It does not replace the enterprise MES \u2014 it coexists with it on the lines where MES was never going to be deployed. The deployment pattern is complementary: MES on the high-compliance lines, lightweight OEE on the operational-efficiency lines, with consistent OEE methodology across the two so that corporate reporting can aggregate results.<\/p>\n Stellantis, Alstom, and Hutchinson each adopted TeepTrak on this rationale. The specific lines vary \u2014 stamping, assembly, specialized fabrication, paint prep \u2014 but the rationale is consistent: MES was not going to reach these lines, and paper-based OEE was producing unreliable data that stalled improvement programs.<\/p>\n The common thread across these enterprise deployments is that most of them were initiated through a consulting engagement, not through a traditional vendor sales motion. An operations consulting team \u2014 BCG, Sia Partners, an internal corporate ops group \u2014 would identify the measurement gap during a diagnostic and propose a lightweight OEE POC as the fix. TeepTrak would run the 48-hour POC on two or three lines as part of the engagement. The POC results would be included in the diagnostic deck. The client would authorize a scaled deployment \u2014 typically 10-30 lines across one or two plants \u2014 on the back of the demonstrated data quality improvement.<\/p>\n This motion is meaningfully different from the enterprise MES RFP process. It is faster (weeks instead of quarters), it is lower-commitment at each step (POC is reversible, RFP commits the client for years), and it produces measurable operational data before the vendor decision is finalized. For enterprise clients who had been burned by MES overcommitment in the past, this sequence felt materially lower-risk.<\/p>\n For the consulting firm running the engagement, the mechanism is a positive reinforcement loop. The firm looks better to the client because the diagnostic produced an implementable fix within the engagement. The client’s operations team looks better internally because they delivered visible OEE improvement faster than the organization had seen before. The vendor \u2014 TeepTrak \u2014 looks better to the next consulting firm that encounters a similar client need, because the reference list keeps compounding.<\/p>\n Instant download. No email confirmation needed.<\/p>\n \n The consultant-led deployment mechanism<\/h2>\n
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