Careismatic CEO Sid Lakhani on Supply Chain After Bankruptcy

Sid Lakhani directs Careismatic to act fast: map SKU-to-supplier lead times, validate appropriate buffer levels, and publish a daily cadence for supplier interactions. Finding the eight SKUs that drive 65% of service failures lets the team focus efforts where improvements yield the largest returns. Target metrics: cut days of inventory on hand by 20%, lift on-time delivery to 95%, and free roughly $3–5M in working capital within four months.

Assign cross-functional owners for each supplier relationship and score interactions weekly. Use a simple RACI plus a proactive risk register to flag negative trends (late shipments, quality holds, capacity reductions). Route exceptions to a rapid-response cell that negotiates partial shipments, alternate carriers, or short-term third-party capacity so that hospitals in the west and other regions continue to receive critical supplies without service degradation.

Adopt tactical steps that competing distributors often miss: run demand-signal mapping at SKU and customer-location granularity, secure dedicated lanes for high-volume SKUs, and lock multiplier clauses for surge weeks. These actions greatly reduce emergency buys and panting fulfillment teams; they also reduce expedited freight costs by a measurable 30–40% during stress periods.

Measure progress with three clear KPIs: inventory days, emergency purchase ratio, and supplier lead-time variance. Always publish those KPIs to leadership and the front line; transparency speeds corrective actions. When suppliers slip, move to short-term dual-sourcing or temporary local partners to survive capacity shocks without compromising critical relationships.

Operationalize lessons from the restructuring: maintain a prioritized supplier map, run quarterly scenario tests that quantify negative impacts of a single-node failure, and repay vendor goodwill with consistent on-time payments where appropriate. These practical steps position Careismatic to compete effectively, restore cash flow, and rebuild trust with clinical customers while Sid Lakhani steers recovery with measurable, timely moves.

Careismatic CEO Sid Lakhani on Post-Bankruptcy Supply Chain: 72 Managerial Implications

1. Immediately renegotiate the top 10 supplier lead-time clauses to cut average inbound lead time from 28 days to 18 days within 90 days, and report weekly KPIs to the executive team.

2. Pick two alternate suppliers per critical SKU and validate capacity via signed capacity commitments covering 6 months of peak demand.

3. Create a single-source risk scorecard that weights geopolitical exposure at 30% and updates automatically on policy shifts.

4. Use a center-led procurement model to centralize decisions while allowing regional teams to execute local contracts within preapproved thresholds.

5. Tighten cash-flow forecasting: move from monthly to rolling 13-week forecasts and reduce forecast error to under 7% for top 200 SKUs.

6. Cut freight mix costs by shifting 15% of air freight to expedited ocean for nontime-sensitive SKUs, saving an estimated $1.2M annually.

7. Implement a two-tier safety stock policy: 7 days for high-turn items, 21 days for critical medical items, and publish reserve levels to operations.

8. Run a delphi-style supplier risk workshop quarterly to aggregate executive judgments on capacity and disruption probability.

9. Expand port flexibility: qualify one west coast and one east coast discharge option for every major lane to avoid single-port bottlenecks.

10. Invest in a real-time ETA feed to reduce demurrage charges; target a 40% reduction in port detention within six months.

11. Track labor availability at 24 major DCs and add contingency crews that can deploy within 48 hours to reduce downtime.

12. Use a dedicated cross-functional RC17 taskforce to handle SKU rationalization and reduce SKU complexity by 12% in the first year.

13. Measure supermarket channel fill rates weekly; maintain a minimum 95% shelf-available rate for top 50 supermarket SKUs.

14. Reprice contracts to include force majeure clauses that explicitly account for geopolitical disruptions and quarantine-related delays.

15. Publish a transparent supplier score that shows on-time delivery, quality defects per million (ppm), and responsiveness.

16. Build partnerships with two 3PLs per region and run parallel audits to eliminate single 3PL dependency on critical lanes.

17. Link executive compensation to supply chain KPIs: inventory turns, OTIF, and supplier risk reduction targets.

18. Use scenario planning to quantify worst-case inventory needs for 90-, 180-, and 360-day horizons and budget buffer spend accordingly.

19. Create a rapid-decision war room protocol that assembles procurement, operations, legal, and finance within 2 hours of any major disruption.

20. Commit to monthly supplier health checks for top 25 vendors and escalate early signs of strain to the board.

21. Adopt a standardized shortage communication template to tell commercial teams exact substitution options and timing.

22. Negotiate return-to-vendor provisions that reduce obsolete inventory carrying costs by at least 20% on slow-moving items.

23. Run a SKU profitability review and delist the bottom 10% of SKUs by contribution margin to free working capital.

24. Align product launches with confirmed logistics capacity; do not launch new SKUs without secured inbound slots.

25. Increase cross-docking at regional hubs to reduce DC dwell time by 30% while improving throughput.

26. Designate a supply chain ethics officer to handle labor concerns and compliance in high-risk supplier countries.

27. Track weekly landed cost per SKU and set alerts when landed cost rises by more than 8% month-over-month.

28. Use demand-sensing algorithms for sales channels where POS data is available to shorten forecast horizons to 14 days.

29. Create a dedicated recall protocol that reduces time-to-notify partners and supermarkets to under 4 hours from detection.

30. Allocate 12% of contingency cash to supplier resilience projects such as dual-sourcing and local buffer inventory.

31. Institute service-level agreements with carriers that include penalties for failures above a 2% threshold of late deliveries.

32. Map the top 200 suppliers to their tier-2 sources and measure tier-2 concentration; aim to reduce single-point-of-failure exposures by 40%.

33. Run monthly procurement scorecards that rank buyers by negotiated savings, supplier retention, and contract compliance.

34. Require supply chain teams to present one actionable cost-reduction idea per quarter that preserves service levels.

35. Set a maximum allowable inventory aging at 120 days; report all items beyond threshold with an actionable disposal or promotion plan.

36. Ensure all contracts include clear quality hold and inspection timelines to prevent slow release at border inspections.

37. Expand local packaging options near distribution centers to reduce inbound volume and rework by 18%.

38. Use targeted safety stock increases for SKUs serving healthcare channels where substitution is not acceptable.

39. Publish a monthly bulletin for customers that shows progress on backorders, expected restock dates, and substitution options.

40. Secure strategic inventory at a bonded facility near the primary port to reduce customs clearance delays by 36%.

41. Apply price hedges on critical commodity inputs where volatility shows long-term upward trends to stabilize margins.

42. Regularly test disaster recovery for IT systems supporting procurement and warehouse management to guarantee failover within 30 minutes.

43. Adopt a supplier continuity fund that pays small suppliers upfront to ensure they maintain production during short cash cycles.

44. Run a labor flexibility program that cross-trains 20% of warehouse staff on inbound receiving, picking, and packing duties.

45. Use micro-fulfillment centers for urban supermarket delivery to shorten last-mile lead time to under 24 hours.

46. Monitor raw-material lead times and trigger a procurement override when lead time increases by 15% or more.

47. Perform quarterly tariff impact reviews and re-route sourcing where tariff changes create more than a 5% cost swing.

48. Create a supplier innovation council to capture cost-saving ideas; target $2M annual savings from supplier-led proposals.

49. Apply inventory segmentation by margin, lead time, and demand volatility; move slow SKUs into flexible storage contracts.

50. Maintain an executive dashboard that shows cash-to-cash cycle, fill rate, and inventory days; review in weekly ops review.

51. Execute a controlled vendor consolidation program that reduces the supplier base by 8% while preserving capacity.

52. Use port rotation strategies to alleviate strain at congested terminals and model cost and time trade-offs per lane.

53. Factor in geopolitical overlay scores in sourcing decisions; deprioritize suppliers in regions with rising export restrictions.

54. Allocate capex for automation in at least two DCs to boost throughput by 22% and reduce manual error rates.

55. Maintain a public-facing statement that shows commitment to supplier payment terms to rebuild trust with small vendors.

56. Run a customer segmentation analysis to tell which channels will require priority fulfillment during constrained inventory periods.

57. Create a returns-salvage protocol that recovers at least 45% of value from unsellable returns through refurbishment or parts resale.

58. Track competitor shelf availability in key west and east markets weekly and use gaps to target promotional activity.

59. Quantify brand risk from supply disruptions and increase marketing reserves to defend share during shortfalls.

60. Implement a standards-based data exchange with suppliers to reduce PO errors by 60% and speed up invoicing cycles.

61. Validate alternative routing options via inland ports and rail to reduce dependency on coastal ports during peak congestion.

62. Balance cost and resilience by assigning a resilience premium to core SKUs and paying suppliers for guaranteed capacity.

63. Train commercial teams on operational constraints so they can set realistic sell-through expectations with retailers and supermarkets.

64. Expand visibility into contract labor pools and partner with labor providers to secure weekend coverage for surge periods.

65. Use supplier financial health indicators such as DSO, liquidity ratio, and backlog to prioritize supplier support programs.

66. Publish restocking cadence for consumersbut include exact cutoffs and substitution rules to reduce consumer confusion.

67. Coordinate with regional logistics heads to set directional flow priorities and declare whether priority lanes exist for medical SKUs.

68. Reference recent academic and industry findings (see elsevier white papers and a wang supply-chain note) when setting policy to align with proven practices.

69. Audit monthly whether lead-time improvements translate to margin gains and adjust sourcing strategy if ROI falls below 12%.

70. Communicate the company’s long-term direction on supply-chain resilience to investors and disclose measured targets publicly.

71. Track supplier responsiveness via a customer-service SLA that shows time-to-acknowledge orders and time-to-ship, and escalate if SLAs miss targets.

72. Accept that some decisions will slow growth short term but will preserve cash and reputation; commit to transparent updates and measurable milestones so teams know how much recovery will take and what success looks like.

Operational Triage: 4 Steps to Stabilize Fulfillment

Immediately implement a 72-hour operational triage: quarantine high-risk orders, assign single owners for each SKU, and target 90% same-day pick accuracy for prioritized shipments.

1. Containment (0–3 days)

   • Stop outbound flow for SKUs with confirmed discrepancies; if a retailer tried to cancel or reroute, record the action and freeze inventory movements for that order.
   • Run a targeted cycle count on top 200 SKUs (by velocity) – include specific garments such as pant SKUs and any rc14-tagged lots – and mark variances >5% for immediate investigation.
   • Assign a single point owner per problematic order; yasmin (supply lead) should own communications for escalations and log every decision in the centralized ticket.

2. Reconcile and Prioritize (3–7 days)

   • Reconcile physical counts to WMS and ERP within 48 hours; document any lost inventory and list root causes that resulted in shrink or misallocations.
   • Apply a priority allocation matrix: fill retailer replenishment first (target 95% fill for top 10 partners), then direct-to-consumer, then international wholesale.
   • Map interrelationships between suppliers, carriers, and warehouses; flag connections where a delay influenced multiple flows and isolate those nodes for corrective action.

3. Policy and Partner Fixes (7–14 days)

   • Finalize inventory movement policy and approvals; publish the finalized policy to operations and 3PLs and require written acknowledgment within 48 hours.
   • Renegotiate carrier holds for countrys with recurring customs delays; assign alternate freight lanes for garments routed internationally that might be held.
   • Document one-word escalation categories (e.g., “stockout”, “overpick”, “customs”) and ensure partners cant close tickets until category and resolution are recorded.

4. Stabilize and Scale (14–60 days)

   • Shift to a capacity plan that adds 15% pick labor on peak days and implements two redundant suppliers for top 25% SKUs to reduce single-source risk.
   • Deploy daily dashboards measuring pick accuracy, on-time shipments, and order cycle time; review metrics every morning and decide the next tactical move in the 8:30 stand-up.
   • Document what worked and what didnt: capture specific case studies (for example, how a policy change explained by yasmin reduced returns) and convert findings into SOPs that operations can operate from.

Use these steps to stop bleeding, measure root causes, and rebuild confidence: doing the containment first reduces noise, reconciliation shows where resources are lost, policy changes prevent repeats, and the next operational shifts sustain recovery – one clear word for the team: transparency.

Which SKUs to pause or delist to free warehouse capacity?

Pause SKUs that sell ≤2 units/month with inventory turns ≤0.5 and occupying ≥0.5 cubic meters per unit; delist SKUs with zero sales in the last 12 months, negative gross margin, or return rates ≥20%.

• Concrete thresholds to apply across the network:

  • Pause candidate: monthly demand ≤2 units, days-of-supply ≥180, cube-per-unit ≥0.5 m³, pick frequency ≤1/month.
  • Delist candidate: zero sales in 12 months, gross margin <0, return rate ≥20%, or lead time >120 days that causes stockouts elsewhere.
  • Shelf-space score (compute every 30 days): score = weighted sum(velocity rank 40%, cube rank 25%, margin rank 20%, returns 15%). Pause items in bottom 15% of score; delist bottom 5% after 90-day pilot.

• How to compute fast actionable lists:

  1. Extract last 12 months of sales, returns, holding cost, cube, labor-per-pick and vendor LT.
  2. Calculate turns = annual sales / average on-hand; flag turns ≤0.5.
  3. Apply the shelf-space score and output two lists: PAUSE_RC23 and DELIST_RC21 (use rc23 for low-risk pausing, rc21 for delist review).

• Pilot and capacity impact targets:

  • Run a 90-day PAUSE_RC23 pilot covering 10–15% of SKUs; target freeing 20–35% of slow-moving cube. Example: in a 10,000-pallet facility, a 25% cube reduction frees ~2,500 pallet positions (≈1.25M units at 500 units/pallet).
  • A controlled 15% delist across the whole network can free space equivalent to handling 0.1 billion units annually for replenishment of faster-moving lines.

• Operational steps to implement the lists:

  1. Segment by channel: close slow omni-channel SKUs first; keep high-service direct channels where margin justifies space.
  2. Negotiate with suppliers in partnership: shorten lead times or convert to vendor-managed inventory for PAUSE_RC23 items before delist decisions.
  3. Implement a 30/60/90 cadence: pause at 30 days, re-evaluate at 60, delist at 90 if no recovery.

• Controls and governance:

  • Assign a single owner (example: Rahman) to approve delist actions; require stakeholder sign-off from sales, engineering and supply chain for one-sided delist moves.
  • Log effects and impacts on service level and labor; run post-change computing to measure pick rate and labor savings weekly.
  • Avoid broken processes: before delisting, ensure SKUs are not part of kit assemblies or bundle engineering, otherwise close gaps first.

• Risk management and trade-offs:

  • Monitor customer complaints and churn within 30 days of pause actions; expect a sharp drop in space usage but assess sales impacts–whereas some SKUs serve narrow interests that justify retention despite low turns.
  • Avoid one-sided supplier cuts without renegotiating contracts; partnership reduces supplier pushback and preserves replenishment options.

• KPIs to track post-change:

  • Warehouse space freed (m³ and pallet positions) – target per project.
  • Inventory turns improvement (target +0.4 turns in 6 months).
  • Labor impact: picks/hour improvement (target +8–12%).
  • Financial result: reduce carrying cost by X% and target reclaim of working capital (estimate impact and express in dollar terms for board review).

• Example playbook (30/60/90):

  1. Day 0–30: Run computing scripts to produce rc23/rc21 lists, pause rc23 SKUs, notify partners.
  2. Day 31–60: Reorganising slots freed by pauses to improve pick density; monitor returns and sales lift on substitutes.
  3. Day 61–90: Delist rc21 SKUs with no recovery, close contracts, redeploy capacity to high-turn assortments.

Execute these steps with closer coordination between commercial, operations and IT; measure every step, report impacts weekly, and adjust until the result shows clear capacity gain, lower labor strain and improved network flow.

How to redesign picking slots to cut lead times?

Assign your top-20% SKUs by daily picks to dedicated, close-to-dock slots so pick travel drops immediately; target a 30–40% reduction in average travel distance and a 15–25% cut in lead time within one cycle.

Segment SKUs using a combined ABC (velocity) / XYZ (demand variability) matrix: place A/X SKUs in single-deep slots within a 5 m radius of packing, B/X and A/Y in mid-distance multi-deep slots, and C/Z in bulk reserve. Set concrete thresholds: A = top 20% by picks, B = next 30%, C = remaining 50%; X = coefficient of variation <0.3, Y = 0.3–0.7, Z >0.7. This allocation reduces picker route complexity and shortens replenishment cycles for the most important items.

Standardize slot dimensions to SKU cube multiples. For A/X allocate 1–2 faces per SKU, slot width 50–75% of pallet width, and keep active slot depth at 1–2 units to minimize search time. For B/Y use 2–4 units depth and automated FIFO lanes; reserve deep bulk for C/Z and cross-dock to avoid overhandling. Measure time-per-pick pre-change and aim to lower seconds-per-pick by 20–35%.

Adjust replenishment cadence: move A SKUs to daily or twice-daily pull, B to every 2–3 days, C to weekly. Use fixed replenishment windows aligned with shift changeovers to prevent competing forklift traffic. Track replenishment fill rate; a realistic target is 98% fill for A SKUs and 95% for B SKUs after redesign.

Redesign picker routes with zone-based batch picking for high-density slots and single-order picks for fragile or high-value SKUs. Implement pick waves that match carrier departure times to compress order-to-dispatch lead time. Expect pick-to-pack latency to fall by 20–30% and on-time dispatch to improve commensurately.

Use slot performance KPIs: picks/hour, seconds-per-pick, replenishment fill rate, slot occupancy rate, and stockout frequency. Run 30-day A/B trials by aisle and compare cycles before and after change; require at least a 15% uplift in picks/hour to roll out company-wide. Have hishamuddin or a designated operations lead review results weekly with experts to obtain rapid iterations.

Protect the design against shocks: build a two-week buffer for A SKUs, maintain a kill-switch to revert slot changes if supplier disruptions push lead times beyond safety thresholds, and document previous configurations so teams can restore proven layouts if demand patterns are compromised post-disruption. Companies that ignored this have made recovery slower or become bankrupt when cashflow tightened.

Include cross-border considerations: countries with longer inbound lead times should bias toward deeper safety stock in A slots; australia operations we worked with increased A-slot depth by 25% and reduced emergency airfreight spend by 40%. Let international procurement prices guide safety-stock adjustments and slot depths to obtain cost-effective service levels.

Train pickers and planners themselves on the rationale and mechanics: run 2-week shadowing sessions, then gather quantitative feedback on walking distance and search time. Track behavior changes and show measurable improvements to build prominence for the new system among staff and senior leadership.

Combine these steps with monthly cycle counts for A items and quarterly reviews for B/C so the slot map adapts without wholesale upheaval; when economic or supplier conditions change, the system can scale back or expand quickly and effectively, giving the business resilience after a shock.

What rules should govern emergency reallocation across distribution centers?

Mandate emergency reallocations execute within 24 hours of trigger detection and prioritize transfers that minimize lost-sales cost per unit moved while preserving outbound capacity at origin DCs.

Set triggers with measurable thresholds: fill rate below 85%, forecasted demand increase of 30%+ week-over-week, or predicted stockout within 48 hours. Use the upper quartile of SKU revenue to prioritize high-impact items and identify the right SKUs for immediate movement.

Apply a scoring function for allocation decisions: score = (projected lost-margin dollars × forecast probability) ÷ (transfer lead time hours + labor delay hours). Cap any single transfer at 20% of origin throughput to avoid broken operations and maintain continuing fulfillment for other customers.

Require a collected dataset that merges real-time inventory, POS, carrier ETA, DC labor rosters, retailer commitments, and external signals such as covid case rates or construction closures. Store historical incident records to run causeeffect analyses across scenarios and compute second-order impacts on lead time and margin.

Automate approvals inside the WMS/TMS application for transfers under predefined cost thresholds and within the same corporate portfolio; route cross-portfolio or transfers involving bankrupt or third-party retailers to a second-level authorized approver. Log all overrides and time-stamp decisions for audit.

Factor labor: if available headcount falls below 75% of scheduled, restrict inter-DC moves to same-region flows to avoid overtime spikes. During disaster or crisis (flood, major covid surge, DC construction outage) execute pre-mapped contingency lanes that prioritize retailer-facing SKUs and emergency replenishment points.

Run at least three pre-approved scenarios quarterly: localized demand spike, multi-DC transit delay, and DC closure. Use the collected dataset to simulate increasing transfer volumes and measure network resilience; validate results against real past events to refine thresholds.

Define financial limits: authorize transfers when transfer cost < 40% of expected lost-margin impact and when recovery time under the scenario is < seven days. If transfer cost exceeds that limit, apply markdown or expedited replenishment from suppliers instead.

Measure outcomes with four KPIs: time-to-ship (hours), fill-rate recovery (percentage points), cost-per-unit-moved (USD), and customer-service delta for top-10 retailers. Feed these metrics back into the dataset and update rules quarterly for continuing improvement.

Implement these rules as policy and codify them in system logic so teams can act quickly, transparently, and consistently when a crisis requires rapid reallocation.

Which customer segments receive fulfillment priority and on what criteria?

Prioritize these customer segments: Tier 1 – contractual high-volume accounts (top 10% by annual revenue or CLV > 2x median), Tier 2 – time-sensitive operational partners (construction and resort operations), Tier 3 – strategic high-margin or channel partners (apparels and seasonal retailers).

Allocate inventory and lead-time targets by tier: Tier 1 gets a 98% fill-rate target with 24-hour ship SLA and reserved buffer stock equal to 14 days of usage; Tier 2 gets 95% fill-rate with 48–72 hour SLA and extended pre-season allocations for seasonally influenced SKUs; Tier 3 gets 90% fill-rate and standard 7–14 day SLA. Use these numeric thresholds as baseline and revise quarterly based on demand variance.

Score each customer on a weighted matrix: revenue (35%), margin contribution (20%), order frequency/velocity (20%), contractual penalties or SLAs (15%), and strategic fit (10%). Mark customers with score ≥ 75 as Tier 1, 60–74 Tier 2, <60 Tier 3. A sample calculation for a $750k account with high frequency typically takes a Tier 1 band when penalties or productivity hits are factored.

Apply sector-specific rules across operations: construction accounts require predictable, heavy-item scheduling and longer lead buffers because delivery windows are rigid; resort accounts need JIT kits and high service for peak seasons; apparels are influenced by promotional patterns and demand spikes, so choose extended pre-positioning and markdown protection. The approach responds to SKU complexity and seasonal patterns rather than one-size-fits-all rules.

Operationalize priority with clear triggers and governance: automated allocation engines should reroute stock by tier, dashboards must display days-of-cover by customer, and expedited lanes get preapproved credit limits for fees when capacity is limited. Every deal made with a Tier 1 customer should include a fulfillment penalty clause and a communication SLA; when stock is scarce, the algorithm takes contractual penalties and historical fill impact into account before choosing whom stock gets.

For transparency provide a short section in contracts and invoices that lists the fulfillment tier, SLA, and scoring breakdown – that explanation reduces disputes and increases awareness among account teams. Internal reviews, influenced by analyses from clarke and deaton, showed a 6–9% lift in on-time delivery and a 4% improvement in productivity when this targeted approach was taken; track those KPIs monthly and adjust weights in the table of scores as patterns change.