Demand Planning
Demand Planning allows the creation of a responsive system that reacts rapidly to the needs of the market, such systems ensure high degree of service levels with the customers while simultaneously maintaining low levels of inventory across the Supply Chain.Schedule a FREE Demo
The Demand Planning Module is a collaborative tool that allows for a consensus demand to be arrived at across the organization. The first step towards Demand Planning is arriving at the statistical forecast.The Module applies various methods of forecasting on the historical Sales data to arrive at the forecast in the coming months. The forecasting can be done at various levels such as SKU-Depot / Brand-Region / SKU Region etc.The tool also allows the Top Down numbers as well as recent history to be displayed along with the statistical forecast. Finally, the tool allows for forecast updation using a Bottom Up approach by the Sales person. This ensures that ground realities are taken into account.The Tool also allows for rationalization of the forecast at the higher Area/Region level in line with rolling sales plan etc. that is Top-Down Rationalization. 
Features and Key Benefits
Model Details
- df
Inward and Outward process
- Forecasting at multiple Hierarchies e.g. SKU-Location, SKU-Sales Office
- Various Forecasting Techniques integration with R
- Selection of Techniques based on different Error Measures with ability to add custom Statistical Techniques
- Collaborative Bottom Up Planning and Top Down Demand
- Normalisation as per Organisation Design
- Classification of SKUs according to various methods
- Super-session allows linking of old to new items to provide meaningful history for effective forecasting new product
- Data viewed in units, cost, selling price, margin, volume, weight, and percentages making up aggregate
- Allows for Promotion data to be entered; can be subsequently used for Elasticity and Forecast normalisation
- Workflow designed to ensure communication across organisationPerformance measurements allows for responsive corrective action
One End-to-end System
- Forecasting Process put in place so as to ensure that forecast is scientifically calculated, and the collaborative element ensures that the forecast agreed upon is based on consensus. This improves Forecast Accuracy
- Different techniques along with outlier detection allows for the best forecast to be generated and selected
- Forecasting helps in better Production Planning and Replenishment Planning which in turns allows for better inventory planning resulting to lower lost sales and lower inventory carrying cost.
- The tool allows for analysis of forecast vs actual. In addition, it also allows for forecast comparison between months within the forecast horizon.
- The tool aids in forecasting of new products as well as allows for forecast adjustments to account for marketing / sales spends.
Key Customers and Testimonials
Inquizity helped us in both technical and functional domains. They came up with innovative ideas on reducing our logistics costs, and improving our production mix.With the help of Inquizity, we developed several solutions which are helping us in inventory, logistics, route optimization, profit maximization across plants, on an integrated platform 
Ashish Desai
CIO, Aditya Birla Group
We evaluated standard solutions from other vendors, and also looked for other alternatives. What we realized was those vendors did not have the technical capability to suit our customized requirements.Plus, in the long-run, the time, cost and efforts we had to invest was much more.Inquizity offered us complete flexibility and customization as what we needed
Sukanta Padhy
Supply Chain Chief, ATG
Case Studies
Crompton
Simultaneous planning for finite capacity and material for APIs and Formulations.
ATG
Optimize planning of product mix to minimize changeovers considering various planning and production constraints.
Flexible Engagement Models
Service Model
- Product run by the Inquizity team
- Product not owned by the Client
- Set-up cost
- Client pays a monthly fees which includes rental, service and infrastructure cost
Subscription Model
- Product run by the Client
- Product not owned by the Client
- Set-up cost and implementation cost
- Client pays a monthly fees which includes rental cost and infrastructure cost
On-Premise Model
- Product run by the Client
- Product not owned by the Client
- Set-up cost and implementation cost
- Client pays an Annual Maintenance Fees
About Inquizity
Inquizity (formerly Indus Momentus Business Solutions) is into S&OP and Business Process Automation SolutionsAbout dataSAVI
dataSAVI is Inquizity’s low-code cloud solution which rapidly builds applications to automate your day-to-day business operationsAddress
3rd Floor Stellar tower, Sion Panvel Road,Opposite K Star Mall, Chembur, Mumbai,Maharashtra 400071Contact
info@inquizity.com+91-9833257112
Copyright
Copyright (c) 2020 Inquizity Metanoia OPC Pvt. Ltd.GST: 27AAECI6558A1ZNSchedule a FREE Demo
Demand Planning
SOLUTIONS DESIGNED TO SYSTEMATICALLY ESTIMATE MARKET DEMAND
Be it New Product Development, Planning, or Promotions, implementing collaborative Demand Forecasting provides you with statistical / ML / AI data to support the course of action in the medium term.
Description
Demand Planning comprises key step of arriving at a baseline number. This is done by using Statistical and ML/AI methods. The Module applies various methods of forecasting on the historical Sales data to arrive at the forecast in the coming months. The forecasting can be done at various levels such as SKU-Depot / Brand-Region / SKU Region
Benefits
Features
Multiple Heirarchy
Forecasting at multiple Hierarchies e.g. SKU-Location, SKU-Sales Office, Brand-Channel etc.
Supersession
Supersession that allows linking of old to new items to provide meaningful continuity in history for effective forecasting new product
Statistical Methods
Variety of Forecasting Techniques using efficient Python to take care of different distributions such as seasonality, promotions etc. Also allows for Outlier Detection
Classification of Products
Dynamic Classification of Products across Runner / Repeater / Stranger using different parameters of frequency, variability etc.
ML / AI Methods
Selection of different AI / ML Methods for cases where ML can be implemented
Choice of Error Methods
Selection of Techniques based on different Error Measures with ability to add custom Statistical Techniques
Some Customer Cases
On the quantitative side, we have integrated the powerful Statistical and Graphical Modelling libraries of Python. We have also connected to ML / AI libraries of WML / Google / AWS to enables the application of a variety of statistical and ML/AI techniques for different situations
Consumer Electrical Company
Enhanced visibility and transparency via S&OP suite for a consumer electrical manufacturer
Speciality Tyre Company
Implemented Demand Forecasting and Demand Aggregation for the smooth function for the manufacturing unit
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