DATA SCIENCE PRODEGREE PROJECT
For Demo of Project click here : https://winpredictionapp.herokuapp.com/
IT firms compete for winning large deals by designing and proposing solutions to their clients. These deals often differ from each other in terms sector of the client, solution to be delivered, technology to be used and the scope of the project. The deal value can reach up to millions of dollars, which leads to highly competitive bidding processes. Even a marginal improvement in the win rate can result into substantial revenue addition for IT firm. By predicting the probability of winning a deal, the engagement teams can prioritize the pipeline of opportunities to staff the most attractive options first. With the probability of winning known in advance, deal engagement manager can ensure that for the most profitable deals there are resources available.
Your Organization puts in a lot of effort in bidding preparation with no indications whether it will be worth it. With multiple bid managers and SBU Heads willing to work on every opportunity, it becomes difficult for the management to decide which bid should be given to which bid manager and SBU Head. You are hired to help your organization identify the best bid manager-SBU Head combination who can convert an opportunity to win with the provided data points.
- Objective 1: Predictive Analytics - Build a ML model to predict the probability of win/loss for bidding activities for a potential client.
- Objective 2: Prescriptive Analytics – Identify variable/s that are most likely to help in converting an opportunity into a win.
Based on the data available i build a model to predict the bidding outcome. This will help your organization decide whether the bid manager and his team should invest their effort working for the win.
Also there are multiple bid managers working with a SBU Head and vice versa. Based on the data i also need to identify the SBU Head-Bid Manager pair which will have the highest winning probability for the bid.
Column Name Description
- Client: Category Industry in which the client works
- Solution: Type The solution group the client requires
- Deal Date: The date the opportunity was created
- Sector: The sector for which the solution is to be provided
- Location: Client location
- VP Name Sr. Manager or VP: which is dealing with the client
- Manager Name: Manager of the team working on the project
- Deal Cost: The initial cost of the deal
- Deal Status Code: Final status of the deal(won/lost)