Analytics for Supply Chain & Logistics Industries - Statswork

Analytics for Supply Chain & Logistics Industries

Our objective is to provide top-notch techno-driven clinical research services to diverse industry sectors including biotechnology, medical equipment organizations, and pharmaceutical companies.

Statistical services provided by us to the complex logistics industry have helped them to enhance their operational speed, precision, and dependability when it comes to moving goods. Business statistics have been strategically deployed in the logistical arena with sizable advantages to freight forwarders, 3PLs, 4PLs, shippers, seaports, airports, rail terminals and regulatory bodies too. Logistics is an intrinsic process which generates a large amount of data.


  • Scheduling data
  • Cargo tariff data
  • Ordering data
  • Billing data
  • Maintenance data
  • Fleet mapping data
  • Asset management data
  • RF integration data
  • Storage & allocation data

While most organizations religiously collect and archive data thus generated, the use of such data is restricted only to operational processes. The vast amount of archived data is hardly utilized by logistic companies to optimize their output. We access this vast data repository and apply business analytics with an objective to drive an enhanced supply chain process, guarantee customer satisfaction, that too at costs that are a far cry from what they usually spend.

Our offerings

Cost Saving Analytics: One of the most prominent areas in logistics where cost can be considerably reduced is in fleet maintenance. Large logistics organizations have a large fleet of vehicles which requires timely maintenance and a large fleet literally, spells huge expenditure when it comes to maintenance. By introducing business analytics, we have been able to aid logistic organizations to cut down their maintenance costs to a large extent by gauging and coming up with favorable schedules to conduct preventive maintenance. The advantage of this approach is that it enables logistic companies to evade unnecessary maintenance while undertaking maintenance as and when required that too at pre-defined intervals. Through business analytics, it is possible to compare repair techniques and formulate a cost-effective approach. We also deploy business analytics to conduct root-cause analysis with a view to decreasing possible breakdowns within the fleet. Further, we also use real-time big data business analytics and artificial intelligence algorithms to initiate and execute predictive maintenance and avoid breakdowns in the field.

Labour Planning Analytics: By deploying business analytics we have been able to help logistic firms to allocate their resources appropriately. Statistical analysis tools have been strategically utilized to optimize available resources by understanding their behavior and performance patterns. The results derived from this analysis have been effectively utilized by HR departments to enhance the overall productivity of individual resources.

Risk Analytics

  • Predictive modeling of claims frequency severity
  • Credit scoring
  • Fraud detection and prediction
  • Foreclosure prediction
  • Rating structures
  • Loss ratio analysis
  • Risk-based pricing
  • Statistical analysis for FDA trials
  • Value at risk modeling
  • Elasticity/severity/scenario
  • Collection & Recovery analysis
  • Extreme event modeling
  • Supply chain analytics
  • Trend plotting
  • Demand /manpower forecasting
  • Location-allocation decisions
  • Inventory management
  • Sourcing/capacity/materials/transport optimization
  • Stock replenishment analysis
  • Due date quoting
  • Expediting optimization
  • CPFR
  • Logistics & Distribution analytics
  • Vehicle routing problems

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