Has anyone here seen measurable savings from a specific advanced program? I’m choosing between the MITx SCM MicroMasters (12–18 months) and a targeted mix of CLTD prep plus a 2-day Gurobi network design workshop, aiming to cut outbound freight per order by 3–5% and improve dock-to-stock by about 10%; which path delivered faster, usable ROI for you?
workshop, aiming to cut outbound freight per order by 3–5% and improve dock-to-stock by — same targets here; CLTD plus the 2‑day Gurobi gave us about 4% freight/order in 6 weeks by re‑zoning and modeling carrier breakpoints, and about 9–11% dock‑to‑stock from tightening door assignments and a simple crossdock mask. Start with one step you can ship right after: feed the last 90 days into a small Gurobi model with service-day constraints and cube/weight caps, pilot on two lanes, then roll to your top 10. MITx was great for depth and long-term network design, but real savings didn’t land until month 9; if you need ROI this quarter, the worksho.
My take: I’d lean toward the simplest next step and see if it changes anything this week — if not, you’ve got a clear case to escalate. What would block you from trying that?
CLTD + the 2‑day Gurobi sprint gave us faster ROI — 3.1% freight/order in about 5 weeks after modeling a zone‑skip and right‑sizing cartons, and inbound putaway time down about 8% from a simple receiving SOP we lifted from CLTD. Do a 30‑day “pilot, then scale”: build a lean lane model, test one carrier mix tweak plus one packaging change, and track cents/order and lines/hour. The MITx SCM MicroMasters (https://micromasters.mit.edu/scm/) was gold for long‑term analytics and network design depth, but more marathon than sprint on payback.
Quick example: the CLTD plus a short solver sprint paid off fastest for us, but only after we normalized lane-level data and added a ‘split-shipment penalty’ in the model — netted 3.6% freight/order in about 5 weeks. Do you already track overbox rate and carrier minimum hits by SKU family? If you go this route, fix carton rules and DIM thresholds in your WMS first, then run the model for immediate wins.
Faster ROI came from the targeted mix; after we modeled ‘carrier minimums’, DIM rules, and pallet-height limits in Gurobi, outbound cost per order fell about 3.6% within two months and dock-to-stock improved about 9% after re-slotting fast movers by ASN staging. MicroMasters helped later with broader network strategy, but it’s slower. @moore79 did you also include dock appointment windows?
If speed is the goal, the targeted mix paid off for us, but the single change that unlocked it was adding an ‘appointment miss fee’ and door‑capacity constraint in Gurobi, fed by WMS door‑in/door‑out stamps — this cut receiving‑to‑bin about 10% and trimmed outbound cost per shipment about 3% in about 6 weeks. MITx was great for broader design and career lift, just slower to monetize; do you have appointment‑level data per carrier to wire into the 2‑day sprint?