Business forecasting and reports generation on cloud based CRM using lightning framework


CRM, Leads, Opportunities, business forecasting, Salesforce, Lightning .


Business forecasting is an estimate or prediction of future developments in business such as sales, expenditures, and profits. It also deals with how and what type of business strategies must be employed to get the better results which would be favour of business. Every business activity is affected by wide range of economic activities; every fluctuation in these activities can have drastic effects on profit margins. It is not surprising that business forecasting has emerged as one of the most important aspects of corporate planning. Business forecasting has emerged as a valuable tool for top managers to anticipate economic trends and prepare them for the counter reaction or to help them for gaining effective economic and business benefits.
For example, if managers envision an economic downturn, they can cut back on their inventories, production quotas and hiring. And if they see a probable boom in market they can take necessary measures to attain maximum benefit from it.

Business forecasting has different levels like from annual forecasts to weekly forecasts. These predictions must be accurate up to certain points else it can make uncertain effects that may lead to business downfall. Many experts agree that precise business forecasting is as much an art as a science. Because business cycles are not repetitious, a good forecast results as much from experience, sound instincts, and good judgement as from an established formula. Business forecasters can be, and have often been, completely off the mark in their predictions. If nothing else, business forecasts can be used as blueprint to better understand the nature and causes of economic fluctuations.

Customer relationship management (CRM) involves technology to organize, automate and synchronize pre sales, sales and after sales processes by managing company’s interaction with customers and leads.

CRM tool is very useful in making reports for overdue costs, invoices and also the transactions over the sales processes and also manages these details in atomic way. These financial reports can be turned into business proposals. CRM can give instant views of previous or pipelined sales and also give details about future sales by analysing marketing leads which are converted into sales opportunities. These reports can be utilized by top managers to make business forecasts.

Problem Description:

Business forecasting is done in both ways, manual forecasting and automated forecasting. Many companies use experts to develop judgmental forecasting [1] for use in their operations. Quite often forecasting is then based on the views of analysts or salespeople. However in general, human beings are not good at forecasting. There are several reasons like; People eventually cut corners leading to hasty assumptions greatly increasing the risk of errors, People tend to give undue weight to the most recent data. However manual forecasting can be of benefit in certain situations. In such situations the overriding factors tends to be that the person doing the forecast has some information that is not currently visible in the data, like information about new product with no previous comparable product line, planned promotions, etc.

In almost every instance manual forecasting is used for exception situations; the real issue is that the people doing the forecasting must actually have sufficient time to review every situation properly and to take past data into account. In forecasting it is important to move quickly to automate routine forecasting, and then give your forecast analysts the best tools to dig into the more challenging situations.

When CRM is operated on cloud as multitenant resource, it becomes necessary to use such business forecasting automation which uses less resource but is effectively fast also the forecasted reports must be very easy to understand.

Project Objective:

To develop a standard, cost effective and flexible, business forecasting component for cloud based Salesforce CRM using lightning framework.

This will include:

  • Implementation of salesforce customized CRM.
  • Reports and Dashboards.
  • Forecasting Algorithm.
  • Use of different sandboxes to test the forecasted data.
  • Comparison with existing business forecasting components.

Use of project in current scenario:

Sales process have various steps from prospecting to follow-up, which includes some important steps like preparation for the deal, handling objections and closing of deal. Salesforce CRM includes all steps of sales and service. The component which will be developed so that it can use the data provided by user and generate a forecast report in such a way that would be cost effective and fast enough for cloud environment and can be used by any salesforce developer as the component will be standard and reusable.

Related work done:

From the very earlier time business need forecast on the basis of current progress and previous sales. Lots of work done from development of manual forecasting processes to automated forecasts[1]. Most of the work is done over the sales report generation [2] and on model-driven dashboards [3] which are used to produces interactive reports in both charts and textual format [4]. Business analysis over social media [2], financial timestamps [5] were done before for making sales prediction. Some other work includes extreme machine learning [6] for larger scale prediction and various business intelligent modules [7] were developed for enterprise planning and business forecasting. Customer’s interest with lead conversion to opportunities [8] and Customer retention [9] also used as a value to predict business success,


Project is very useful for the cloud based CRM especially for salesforce users. Algorithm that will be implemented would be very efficient and less costly in terms of server computations and other overheads than the present methods. The lightning framework is new development framework provided by salesforce for the salesforce developers to implement more interactive components which will be used to make interactive forecasting.

Feasibility of approach:

Salesforce provide developers to customize and configure current standard components and also provide many technology frameworks like lightning, platform utilizing Apex language to build cloud apps which can be shared through AppExchange to different salesforce developers. The project will use salesforce CRM and its supportive technologies to build the business forecast component over lightning framework.


[1] Johanna Sma˚ros, Markus Hellstro¨m, “Using the assortment forecasting method to enable sales force involvement in forecasting A case study”, International Journal of Physical Distribution & Logistics Management, Volume 45 Issue 9/10,  page 140-157, 2015

[2] Hyung-Il Ahn, IBM Res. – Almaden, “Sales Prediction with Social Media Analysis”, Global Conference (SRII), 2014 Annual SRII, IEEE, April 2014

[3] Pawan Chowdhary, Themis Palpanas, Florian Pinel, Shyh-Kwei Chen, Frederick Y.  Wu, “Model-Driven Dashboards for Business Performance Reporting”, IEEE EDOC Hong  Kong, 2006

[4] Ramos-Soto, Lama  M., Vazquez-Barreiros B., Bugarin A., “Towards Textual Reporting in Learning Analytics Dashboards”, Advanced Learning Technologies (ICALT), IEEE Hualien, July 2015

[5] K ush R. Varshney and Aleksandra Mojsilovic, “Business Analytics Based on Financial Time Series”, Signal Processing Magazine, IEEE, page 83-93, IEEE, Sept. 2011

[6] Ming Gao,  Wei Xu, Hongjiao Fu, Mingming Wang, “A Novel Forecasting Method for Large-Scale Sales Prediction Using Extreme Learning Machine”, Computational Sciences and Optimization (CSO), IEEE Beijing, July 2014

[7] Velic M. , Marko Velic Initium Futuri d.o.o. Zagreb, Croatia, Padavic I.,  Lovric Z., “Model of the new sales planning optimization and sales force deployment ERP business intelligence module for direct sales of the products and services with temporal characteristics”, Information Technology Interfaces (ITI), IEEE, page 91-96, June 2012

[8] Feng Qian, Linwen Xu, “Constructing Customer’s Value Analysis Model Based on Expert System for Leisure Farms”, CINC ’09, IEEE Wuhan, 2009

[9] Hongmei Shao, Gaofeng Zheng, Fengxian An, “Construction of Bayesian Classifiers with GA for Predicting Customer Retention”, IEEE Jinan, 2008