Use Artificial Intelligence To Set Sales Targets
Setting Sales targets has always been an inexact science, with serious consequences if done poorly. Using AI based advanced analytics might be the answer. Setting the right sale targets for employees is a difficult balancing act, with long term consequences on morale and growth. Setting a target too low, making it easily achievable might cause an employee to not put in the effort. Setting a target too high can be equally problematic, since there is no chance of meeting it. The Salesperson will be discouraged, and just as unlikely to work to their full potential.
In fact. organisations, often lose top Sales talent because of target setting that penalizes success. One common misstep is using past performance as a yardstick. If a top performer overshoots annual target say by 20%, the next year's target is set at 120% of the current year. While next year's target for a Rep who just achieves 90% of this year's target remains unchanged. Not surprisingly, Top performer find unfair and often jump ship. Besides. a compensation plan that grows up slowly at a consistent rate related to company's growth objectives only works in a stable market, stable industry and in a stable region. Companies dramatically improve productivity after adopting advanced analytics to guide compensation.
Many companies are struggling to set ambitious but fair targets to motivate Sales people to deliver organic growth. Some of these companies are using Advanced Analytics to identify the true drivers
of business outcomes and are applying Big Data and Machine Learning to understand consumer demand at an unprecedented level of accuracy and granularity, With such projections, they can establish more meaningful targets.
Artificial Intelligence - An array of approaches that rely on computer systems and Algorithms (set
of rules to be followed in calculations by computer) to handle human tasks -allows companies to
use multiple variables to compute the best targets for the employees, often in real time. Many companies have started using machine - learning to construct AI systems.
Such Algorithms can be of two forms -
1) Supervised Learning - In this manner, using labeled Data, the Algorithms learns to predict the
outcome from Input Data.
2) Unsupervised Learning - In this case, using unlabeled Data, the Algorithms learns the inherent
structure from the Input Data.
Either machine learning approach is only as good as the humans who are setting the objectives
and managing the Data. Companies that succeed with AI tend to -
a) Consider company's broader goal.
b) Identify and collect as much as relevant data as possible.
c) Develop an Algorithm that goes deep.
Whatever the route a company goes, the right Algorithm will use the data to generate a number for each employee. That figure can include an overall target, as well as specific targets for each product line to maximize an employee's productivity while striving towards company's overall goal. While this process is automated, field Sales Managers might need to fine tune the final number.
The success of using such a system depends on two things - Amount of Data a company includes
so as to create the most accurate measures, and Management's confidence, which helps foster buy-
in by Sales Managers.
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In fact. organisations, often lose top Sales talent because of target setting that penalizes success. One common misstep is using past performance as a yardstick. If a top performer overshoots annual target say by 20%, the next year's target is set at 120% of the current year. While next year's target for a Rep who just achieves 90% of this year's target remains unchanged. Not surprisingly, Top performer find unfair and often jump ship. Besides. a compensation plan that grows up slowly at a consistent rate related to company's growth objectives only works in a stable market, stable industry and in a stable region. Companies dramatically improve productivity after adopting advanced analytics to guide compensation.
Many companies are struggling to set ambitious but fair targets to motivate Sales people to deliver organic growth. Some of these companies are using Advanced Analytics to identify the true drivers
of business outcomes and are applying Big Data and Machine Learning to understand consumer demand at an unprecedented level of accuracy and granularity, With such projections, they can establish more meaningful targets.
Artificial Intelligence - An array of approaches that rely on computer systems and Algorithms (set
of rules to be followed in calculations by computer) to handle human tasks -allows companies to
use multiple variables to compute the best targets for the employees, often in real time. Many companies have started using machine - learning to construct AI systems.
Such Algorithms can be of two forms -
1) Supervised Learning - In this manner, using labeled Data, the Algorithms learns to predict the
outcome from Input Data.
2) Unsupervised Learning - In this case, using unlabeled Data, the Algorithms learns the inherent
structure from the Input Data.
Either machine learning approach is only as good as the humans who are setting the objectives
and managing the Data. Companies that succeed with AI tend to -
a) Consider company's broader goal.
b) Identify and collect as much as relevant data as possible.
c) Develop an Algorithm that goes deep.
Whatever the route a company goes, the right Algorithm will use the data to generate a number for each employee. That figure can include an overall target, as well as specific targets for each product line to maximize an employee's productivity while striving towards company's overall goal. While this process is automated, field Sales Managers might need to fine tune the final number.
The success of using such a system depends on two things - Amount of Data a company includes
so as to create the most accurate measures, and Management's confidence, which helps foster buy-
in by Sales Managers.
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