# SyteLine MRP Health Check: Is Your Planning Engine Trustworthy? > Source: https://netray.co/tools/syteline-mrp-health-check > Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems. > Section: Free Tools ## Short answer Diagnose why your SyteLine MRP output is noisy or ignored, scoring data accuracy, parameters, and planner behavior across ten dimensions. ## Category syteline ## Tool **Kind:** assessment **Questions:** #### What is your cycle-count inventory record accuracy? **Help:** MRP output can never be better than the inventory balances feeding it. World class is 98%+. **Options:** ##### 98% or better, verified by cycle counting **Score:** 3 ##### 95-97% **Score:** 2 ##### 90-94% **Score:** 1 ##### Below 90% or we do not measure it **Score:** 0 #### How accurate are your bills of material? **Options:** ##### 99%+ accurate with a formal ECN process **Score:** 3 ##### Mostly accurate; occasional shop-floor redlines **Score:** 2 ##### Frequent discrepancies between BOM and actual build **Score:** 1 ##### BOMs are widely distrusted or incomplete **Score:** 0 #### How well do routing times and lead times reflect reality? **Help:** Inflated lead times are the most common cause of excess inventory and early releases. **Options:** ##### Reviewed against actuals at least annually **Score:** 3 ##### Mostly reasonable; some padded values **Score:** 2 ##### Set at go-live and rarely touched since **Score:** 1 ##### Largely guesses; planners ignore system dates **Score:** 0 #### How large is your open MRP action message (planner workbench) backlog? **Options:** ##### Reviewed daily; backlog effectively zero **Score:** 3 ##### Reviewed weekly; manageable backlog **Score:** 2 ##### Hundreds of stale messages; triaged sporadically **Score:** 1 ##### Thousands of messages; effectively ignored **Score:** 0 #### How reliable is your MRP/APS regeneration process? **Options:** ##### Runs nightly, completes cleanly, results monitored **Score:** 3 ##### Runs regularly with occasional failures **Score:** 2 ##### Fails or produces suspect results often **Score:** 1 ##### Run rarely or manually because output is distrusted **Score:** 0 #### What share of your purchase orders and jobs are expedited? **Options:** ##### Under 10%; expedites are the exception **Score:** 3 ##### 10-25% **Score:** 2 ##### 25-50% **Score:** 1 ##### Over 50%; expediting is the default mode **Score:** 0 #### How are safety stocks and order modifiers (min/mult, order policies) managed? **Options:** ##### Reviewed on a schedule using demand analytics **Score:** 3 ##### Reviewed occasionally for top items **Score:** 2 ##### Set once at go-live, never revisited **Score:** 1 ##### Inconsistent or missing across most items **Score:** 0 #### What percentage of your open shop orders are past due? **Options:** ##### Under 5% **Score:** 3 ##### 5-15% **Score:** 2 ##### 15-30% **Score:** 1 ##### Over 30%; past-due is chronic **Score:** 0 #### How disciplined is your demand input (forecasts and customer orders)? **Help:** Garbage demand in means garbage supply plan out, no matter how well MRP is configured. **Options:** ##### Formal forecast process with measured accuracy **Score:** 3 ##### Basic forecasting; reviewed monthly **Score:** 2 ##### Ad hoc forecasts entered irregularly **Score:** 1 ##### No forecasting; MRP sees demand too late to act **Score:** 0 #### How much do planners actually trust and use MRP output? **Options:** ##### MRP drives daily planning; spreadsheets are rare **Score:** 3 ##### MRP is the baseline with some side spreadsheets **Score:** 2 ##### Planners run the plant from spreadsheets, checking MRP occasionally **Score:** 1 ##### MRP output is ignored entirely **Score:** 0 **Bands:** #### MRP is effectively broken **Min:** 0 **Max:** 24 **Verdict:** Your planning engine is not steering the business; people and spreadsheets are, at enormous hidden cost in expediting, excess inventory, and missed dates. The good news is that environments like this usually contain 3 to 5 fixable root causes rather than dozens, and the payback on fixing them is fast. **Recommendations:** - Stop tuning parameters and fix foundation data first: launch cycle counting and BOM verification programs this month. - Mass-close stale action messages and past-due orders so planners start from a clean, honest picture. - Pick one product line as a pilot: fix its data, run MRP, and rebuild planner trust with visible wins. - Assign a named owner for MRP health with weekly metrics on accuracy, past-due, and expedite rate. - Bring in a SyteLine planning specialist for a 2-3 week diagnostic before attempting broad fixes. #### Struggling: firefighting is winning **Min:** 25 **Max:** 49 **Verdict:** MRP produces output but the organization works around it more than with it. Expediting and manual overrides are absorbing planner capacity that should go into improvement. You likely have solid pockets undermined by two or three systemic weaknesses, most often inventory accuracy, stale parameters, or message backlog. **Recommendations:** - Identify your two lowest-scoring questions; they are almost certainly your root causes. - Institute a weekly action-message triage cadence with a hard ceiling on open messages. - Re-baseline lead times and safety stocks for your top 20% of items by usage value. - Measure and publish expedite rate and past-due percentage monthly to create accountability. - Schedule a parameter tuning workshop with planners so fixes stick culturally, not just technically. #### Functional: working but leaving money on the table **Min:** 50 **Max:** 74 **Verdict:** Your MRP fundamentals are sound and planners mostly work with the system. The remaining gaps are optimization opportunities rather than crises, typically in forecast discipline, parameter refresh cadence, or squeezing out residual expediting. This is the band where advanced tools start paying off. **Recommendations:** - Establish a quarterly parameter review using demand variability analytics rather than gut feel. - Attack the remaining expedite rate with root-cause coding on every expedited order. - Evaluate SyteLine APS or finite scheduling if capacity, not material, is now your constraint. - Pilot AI-assisted demand sensing or exception prioritization to focus planner attention. #### High-performing planning engine **Min:** 75 **Max:** 100 **Verdict:** Your MRP is doing its job: accurate data in, trusted plans out, exceptions managed by process. Manufacturers at this level should protect the discipline that got them here and shift energy toward automation and predictive capability, where the next tier of ROI lives. **Recommendations:** - Codify your data-accuracy and review cadences so performance survives staff turnover. - Automate routine planner actions (order approvals, reschedules within tolerance) to free capacity. - Layer AI agents on top of MRP for exception triage, supplier risk flags, and demand anomaly detection. - Benchmark inventory turns and service level annually against industry peers to keep raising the bar. ## Content **Intro:** This free SyteLine MRP health check diagnoses why your planning output is noisy, distrusted, or ignored, and tells you exactly where to intervene. It is designed for materials managers, planners, and operations leaders running Infor SyteLine or CloudSuite Industrial in discrete manufacturing. Ten questions score the factors that actually determine MRP performance: inventory and BOM accuracy, lead-time realism, action message discipline, expedite rates, demand quality, and planner trust. You get a scored band with specific fixes, ordered by impact, in about three minutes. **Sections:** #### Why MRP fails: it is almost never the software **Body:** In hundreds of struggling SyteLine planning environments, the same pattern repeats: the MRP engine is computing correctly on data that is wrong. Inventory accuracy below 95% guarantees phantom shortages and surprise stockouts. Padded lead times, set defensively at go-live and never revisited, tell MRP to order too early and too much, inflating inventory 15-30%. And once planners stop trusting output, they retreat to spreadsheets, which starves the system of timely transactions and makes the data worse, a self-reinforcing spiral. This assessment weights foundational data questions heavily because no amount of parameter tuning fixes MRP running on a fiction. #### Benchmarks used in this assessment **Body:** The scoring thresholds come from widely accepted manufacturing planning standards and what we observe separates high performers from strugglers in SyteLine shops: **Bullets:** - Inventory record accuracy of 98%+ and BOM accuracy of 99%+ are the recognized thresholds for MRP to be reliable. - High performers keep expedited orders under 10% of releases; strugglers routinely exceed 40%. - Past-due shop orders under 5% indicates a plan the shop can actually execute. - A planner workbench reviewed daily with near-zero stale messages is the single best behavioral predictor of MRP trust. #### From score to fix: how Netray helps **Body:** A low score is actually good news in disguise: MRP problems are among the highest-ROI fixes in ERP, because expediting, excess inventory, and missed ship dates are all directly measurable costs. Netray runs focused MRP recovery engagements for SyteLine: a 2-3 week diagnostic that pinpoints root causes with data analysis rather than opinions, followed by targeted remediation of parameters, data processes, and planner workflows. We also build AI-assisted planning agents on top of SyteLine that triage action messages, flag demand anomalies, and auto-execute routine reschedules, so your planners spend their time on the exceptions that matter. Most clients see expedite rates fall measurably within one quarter. **Cta:** Get a free MRP diagnostic call with a SyteLine planning specialist and turn your score into a 90-day recovery plan. **Faq:** #### Why does SyteLine MRP suggest orders we do not need? **Answer:** The usual suspects are inaccurate on-hand balances, stale demand (old forecasts or orders that should be closed), inflated safety stocks, and order modifiers like minimums and multiples that no longer match real usage. MRP is deterministic: unwanted suggestions always trace back to a data input. Start by auditing the pegging on a few bad suggestions; it reveals the offending input quickly. #### Should we use SyteLine APS instead of classic MRP? **Answer:** APS adds constraint-based, capacity-aware planning and can be a major upgrade, but it amplifies whatever data quality you have. If your assessment score is below roughly 50%, fix inventory accuracy, BOMs, and routings first; APS on bad data produces confident nonsense faster. Shops scoring 70%+ with capacity bottlenecks are the ones that get real value from moving to APS or finite scheduling. #### How long does it take to fix a broken MRP environment? **Answer:** Meaningful improvement typically takes one to two quarters. The sequence matters: clean stale orders and messages in weeks one and two, launch cycle counting immediately since accuracy builds over months, re-baseline lead times and safety stocks for high-value items in the first month, then rebuild planner trust through a pilot product line. Full cultural adoption, where spreadsheets genuinely retire, usually follows within six months of visible wins. ## Search terms syteline mrp problems, syteline mrp not working, mrp health check, erp planning accuracy, syteline aps vs mrp, mrp action messages cleanup, manufacturing planning assessment --- Talk to an engineer: https://netray.co/contact?intent=erp_ai | Machine catalog: https://netray.co/agent/catalog.json