How to make the most of your supply chain and analytics certification
There are mainly three types of analytic approaches to Supply Chain Management, namely, Descriptive Analytics, Predictive Analytics and Prescriptive Analytics. Descriptive Analytics gives us an insight into what has happened earlier in the same or similar business houses for Supply Chain Management. The process is basically acquiring, summarising and rationalising large datasets to project new business insights.
The process of predicting the future with the usage of historical data gathered and then using different statistical tools or computer-based complex algorithms is known as Predictive Analysis. Nowadays Supply Chain Management Certification Course teaches Analytic Tools to prospective candidates. This is to forecast what will happen in the future. And the third mode of Analysis is Prescriptive Analysis.
This Analytics deals with real-time operation research tools to find out the correct decisions that shall lead to the best results in Supply Chain Management. This can be performed by several optimisation techniques. Predictive Analysis is the future trend of Descriptive Analysis, if there is no course correction. When the corrective measures are taken based on operation-based research and model simulation through computer-aided algorithms, the percentage of error in the Supply Chain Management process is reduced and thus the process is called Prescriptive Analysis, which ultimately leads to a 6-Sigma process i.e. a process with minimum error tolerance.
Predictive Modelling in forecasting Supply Chain Elements
Predictive Analytics examines all possible scenarios encompassing demand planning, cost, profit, inventory optimisation, logistics and much more. Predictive Modelling allows companies to gauge anomalies in their Supply Chain network and responds accurately given past conditions.
Predictive Modelling generally leads to two types of forecasting errors – overstocking and understocking. While overstocking creates havoc in the inventory and cash flow for all the stakeholders in the supply chain, understocking tends to make customers unhappy, making them turn towards competition.
Since any business would like to avoid the understocking situation, keeping more stock is better. However, overstocking leads to the Bullwhip effect. Excess inventory increases from retailers to wholesalers to manufacturers to vendors.
Thus in order to make Predictive Modelling more reliable, additional data other than the historical ones are required. Though used in the recent past, Predictive Analysis has proved to be of immense support to the planning team in a manufacturing set-up.
Why do Organisations use Predictive Analytics nowadays?
Most of the business houses operating in Supply Chain Management are using Predictive Analytics in the recent past to increase their profitability percentage and volume. The key reasons are the following –
- The growth of the Information Technology industry has given way to the growth of more and more accurate data.
- The enthusiasm to use the data for business insight has also developed multi-fold.
- Availability of computers.
- Availability of interactive and easy to use & understand software.
- Tougher Global Economic situation.
- Fierce competition and hence the requirement to create uniqueness.
Thus under this present scenario, the Predictive Analytics tool cannot have the luxury of being used by Statisticians and/or Mathematicians. Over the course of time, it has become the default tool for a Business Leader who seeks excellence in operation and also wishes to maximise the bottom line.
Important features of Predictive Analytics
The most important features for which organisations use Predictive Analytics Modelling are Detecting Fraud, Reducing Risk, Improve Operations and Optimising Market Campaigns. The model uses the feature of detecting the location of the error in the respective function; so that it may be course-corrected.
Detecting Fraud - The tool can help organisations in the detection and prevention of criminal behaviours of imposters posing as associated partners or even competitors. These are cyber crimes, which create havoc in the secured database of an organisation.
Reduction of risk - Creditworthiness (credit score, etc.) of a customer or credential (past performance records) of a prospective vendor may be worked out using these tools and hence supports de-risking of business.
Improve Operations - Organisations take the help of this modelling system in cases of asset optimisation and management of inventory and resources. In the hospitality business, capacity utilisation can be predicted for a particular time of the year. Thus hotels can plan their inventory and resources accordingly. Airlines also hike or reduce fares using historical data for a specific time of the year and can make similar arrangements for their assets, as well.
Optimising Market Campaigns - Purchasing habits including quantum and frequency may be recorded by the history data. Thus these records may be used by the organisation to make more efforts for promising customers and lesser for those expected to conclude in cold calls quite often.
Career as Supply Chain Analyst
Prospective candidates should complete an offline PG course or a Supply Chain Management Online Training prior to enrolling themselves in the Supply Chain Management Certification Course. The IIT Supply Chain Management Course at Imarticus which provides live online training will help you to become an expert in this field. The knowledge of Supply Chain Management will help the candidates understand the functional aspects of the core subject while the certification course will help them evolve as Data Scientists or Consultants in Supply Chain Management, depending on the enthusiasm, dedication and exposure of the candidates. There is no second thought that it would be a great and rewarding career.