The growing technology and advancements along with an increased flow of data, is shifting this industrial era 4.0 towards a more data driven strategic process mind set. Within an organisation the most crucial thing is to generate the forecasts in almost all of the planning and decision making processes. Future demand of the products and services, production planning, marketing strategies, resources planning, etc can be considered certain examples for the same, where data plays a vital role.
Forecasting analytics helps domain experts to choose an appropriate time series forecasting method, fit the method based model, evaluate its performance and use it for forecasting. Indeed these analytics are based on the most popular business forecasting methods which enable automation in the same. These include techniques such as; regression models, autoregressive (AR) models, autocorrelation models, analysis of real trends and behaviour patterns, etc.
Thus forecasting Analytics help domain experts to take data driven decisions for driving the business such as;
- Making most of the consumer patterns
- Use the overall data to drive the performance
- Managing risks through analytics
- Building mechanisms and models for repetitive patterns
- Drive analytical transformations
Inventory management analytics on the other hand helps organisations to identify items/parts/products that are trending towards being out of stock, providing a statistical method of stock management, making it more reliable than supplier data. Inventory management / optimization are all about the provision of right inventory, in the right quantity at the right location and in the right time, in order to meet the supply and demand of parts and materials in the organisation. One should always keep in mind that, inventory optimization lies in the volumes/quantity of the inventory transactions, which require an in-depth analysis to identify the key patterns and trends.
Inventory analytics can certainly make use of such pool of data (whether be transactions/incoming/outgoing/etc) to capitalise on an analytical solution for strategic data driven decision making. These analytics will help domain experts to avoid unproductive conditions, excess stock conditions, etc and ensure maximal returns on minimal investments. The key benefits of the same are truly substantial right from quick deep actionable insights, to quantified financial impacts, to optimum automation of the process – all of these leading to an increased cash flow, inventory cost savings & maximum ROI.
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Shall discuss about Cost Optimisation Analytics, in the next article. Happy reading!