Abstract

The most fundamental building block of any organization is Data; data is critical to any organization’s success. Getting data governance and quality right, can significantly improve the quality of sales planning and result in an intelligent data-driven territory allocation process. On the contrary, poor data quality and loose governance models often lead to laborious territory planning cycles, sub-optimal sales rep to account mapping and poor customer experience. Poor data quality could also result in an over- or under-allocation of a sales person’s territory and can result in poor customer experience and even attrition. On the operational side, this could result in poor forecasting, inefficient revenue attribution, tedious reporting exercises (due to lack of data modeling), and a significantly delayed root cause analysis when companies miss financial goals.

Highlights

  • Significantly improve the quality of sales planning and result in Geographical. an intelligent data-driven territory allocation process

  • On the operational case of a subscription model), Revenue, Deal Pipeline side, this could result in poor forecasting, inefficient revenue

  • The following set of best practices are written through a lens of data in a CRM environment

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Summary

By Venketesh Iyer

University of California Berkeley Abstract- The most fundamental building block of any organization is Data; data is critical to any organization’s success. Getting data governance and quality right, can significantly improve the quality of sales planning and result in an intelligent data-driven territory allocation process. Poor data quality and loose governance models often lead to laborious territory planning cycles, sub-optimal sales rep to account mapping and poor customer experience. This could result in poor forecasting, inefficient revenue attribution, tedious reporting exercises (due to lack of data modeling), and a significantly delayed root cause analysis when companies miss financial goals. On the operational case of a subscription model), Revenue (reflecting business), Deal Pipeline (reflecting potential) side, this could result in poor forecasting, inefficient revenue Product adoption attribution, tedious reporting exercises (due to lack of data modeling), and a significantly delayed root cause analysis when companies miss financial goals. The revenue and HR organizations contribute heavily to the planning exercise

Correctness of the Fundamental Data Attributes to Elevate Trust
Findings
Références Referencias
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