Decision Support

DATA DRIVEN DECISION

Data driven decision making is a way of working that values the business decisions backed up by verified and analyzed data. Such governance is possible and the quality of data gathered is ensured. Data driven business decisions make or break companies. Such governance is undertaken in order to be more competitive.

Data should be at the centralized hub of strategic decision making in businesses, whether they are huge MNC’s or small family-run operations. Data can provide insights that help you answer your key business questions.

We believe in data-driven decision making and help our customers strategize their business accordingly and effectively.

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Decision Support Process
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Purchase KPI

  • RM Inventory
  • Based on reason
  • RM for Purchase 
  • RM Purchase influencers
  • Handling times
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Production KPI

  • Capacity utilization
  • Yield
  • WIP Inventory Level by Purchase
  • Process through-put
  • Handling times
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Sales KPI

  • Total Sales Volume
  • Trusted Customers
  • Repeat Customers
  • Sales life turn around time
  • Sales Order Pipeline
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Organization KPI

  • Organization KPI will be derived based on overall performance of all functions.
  • Net Profit Margin/ Operational Cost/ Business Growth Pattern/ Customer Base
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Individual KPI

  • Employee KPI will consider the motivation factor
  • Organization growth
  • Individual growth
  • Gamification based KPI
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Finance/HR

  • PipelineOperational Cost
  • Manpower Cost
  • Material Cost/ Non material Cost
  • Hires
  • Employee performance

Decision Support Process
Purchase
  • Visibility to RM Pricing Y-o-Y, Q-o-Q, M-o-M, W-o-W
  • Supplier (Trader) Quality on RMs (Waste %, Moisture %, etc.)
  • Secondary Market Data
  • Sales Orders (Confirmed and Pre-Order)
  • RM Inventory on Hand and Grade-wise Production Output
  • Recommendations on Qty to Buy and Price-points (location-wise)
Production
  • Visibility to Sales Order Pipeline
  • Consolidate Sales Orders and create a Production Plan after the existing inventory is exhausted
  • Grade-wise production output to fulfil the Sales 
  • Based on Grade-wise output, RM consumption to be planned
  • (Hard) Allocation of On-Hand RM Inventory
  • (Soft) Allocation of RM Inventory reaching the Factory, after factoring for the standard yield
Sales
  • Sales Analysis to aid the Sales person
  • Approaching the RIGHT CUSTOMER at the RIGHT TIME to secure orders
  • Sales numbers by: YoY, QoQ, MoM, WoW, etc
  • Customer buying behaviour in decision support process
  • Sales Team to get automated notification of sales related process.
  • Sales price information
Business value to Customers through business technology
Ensure ROI for the technology interventions and investments
Employee Empowerment through data driven decisions