SALES PIPELINE PREDICTION - Predicting a Pipeline using Time Series and Dummy Variable Regression Models
Bindu Narayan, Deepak Ravindran, Picton Sue, Jayant Das Pattnaik
2012
Abstract
Sales pipeline metaphorically is a pipe through which the opportunities pass on the way to becoming a sale. As the opportunity progresses through the pipe the likelihood of becoming a sale increases. Predicting the sales pipeline is very critical. Accurately predicting the sales pipeline is essential in planning future costs and capacity requirements. Since the sales pipeline is in itself a subjective prediction made by sales reps, predicting the pipeline essentially becomes a problem of predicting a prediction. Most managers do this by solely depending on their sales representatives perception on which business will close. A prediction model was developed using time series modeling to predict the next quarter sales pipeline. The uniqueness of the model is that, it captures two different types of co-existing seasonlaities. A predictive model was created which is refreshed weekly with actual pipeline numbers and is successfully deployed within business.
References
- Tom, Snyder. 2006. White Paper, Rational Forecasting. Martin, Lewis. 2009. Webinar, Principal, 3g Selling.
- Gilmore, Lewis. 2006. White Paper, How To Develop An Effective Sales Forecast.
Paper Citation
in EndNote Style
TY - CONF
JO - Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - SALES PIPELINE PREDICTION - Predicting a Pipeline using Time Series and Dummy Variable Regression Models
SN - 978-989-8425-97-3
AU - Narayan B.
AU - Ravindran D.
AU - Sue P.
AU - Das Pattnaik J.
PY - 2012
SP - 114
EP - 119
DO - 10.5220/0003716201140119
in Harvard Style
Narayan B., Ravindran D., Sue P. and Das Pattnaik J. (2012). SALES PIPELINE PREDICTION - Predicting a Pipeline using Time Series and Dummy Variable Regression Models . In Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-8425-97-3, pages 114-119. DOI: 10.5220/0003716201140119
in Bibtex Style
@conference{icores12,
author={Bindu Narayan and Deepak Ravindran and Picton Sue and Jayant Das Pattnaik},
title={SALES PIPELINE PREDICTION - Predicting a Pipeline using Time Series and Dummy Variable Regression Models},
booktitle={Proceedings of the 1st International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2012},
pages={114-119},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003716201140119},
isbn={978-989-8425-97-3},
}