2,011
16
Analysis Paper, 2 pages (300 words)

Efi analysis

Can we say that to be good in SW is bad in HW When we ran the regression analysis, Software add-on actuals (SW) in terms of hardware actuals for Q1 under new compensation policy, we observed R2 of 0.

227 & coefficient of 0. 982 & correlation coefficient of 0. 477. From this we can say that either both are going in the same direction (+ve or –ve), but not in the opposite way. So to be good in SW does not mean we have to be necessarily bad in HW.

2. Why the intended behavior didn’t happen? a.

No incentive for over achievers (operating beyond the target level for the extra effort put-in) b. It broke the team spirit wherein over achievers were helping under achievers to come on par c. The variable component (based on individual performance) for the software add-ons was only 10% of total.

d. The territory sales figures received from IKON were not accurate. So the tracking of the individual performance measurement was not accurate, which led to SDMs dissatisfaction. e. There has been at the maximum of only a 10% variance in pay.

Also the people who did very well on the hardware (Fiery) targets were not recognized properly ; to make things worse, happened to be in the bottom 50% of the Stacked Ranking Reports which were based on software add-ons target. 3. Recommendations Sales force level – a. We see that SDMs are more technical oriented. This served well when the market was not mature enough. Under as per situation given in the case they need to be more market oriented with sales skills.

The criteria for new recruits should be on marketing skills.

Compensation a. There should be proper recognition mechanisms for people who do well in hardware targets. For example, stacked rankings report for hardware targets. b. Suggested compensation plan – 50% salary fixed, 30% individual performance based variable compensation for meeting hardware targets and 20% individual performance based variable compensation for meeting software add-on targets.

Commission based component for additional software add-ons sales made by over achievers.

Thank's for Your Vote!
Efi analysis. Page 1
Efi analysis. Page 2
Efi analysis. Page 3

This work, titled "Efi analysis" was written and willingly shared by a fellow student. This sample can be utilized as a research and reference resource to aid in the writing of your own work. Any use of the work that does not include an appropriate citation is banned.

If you are the owner of this work and don’t want it to be published on AssignBuster, request its removal.

Request Removal
Cite this Analysis Paper

References

AssignBuster. (2022) 'Efi analysis'. 28 September.

Reference

AssignBuster. (2022, September 28). Efi analysis. Retrieved from https://assignbuster.com/efi-analysis/

References

AssignBuster. 2022. "Efi analysis." September 28, 2022. https://assignbuster.com/efi-analysis/.

1. AssignBuster. "Efi analysis." September 28, 2022. https://assignbuster.com/efi-analysis/.


Bibliography


AssignBuster. "Efi analysis." September 28, 2022. https://assignbuster.com/efi-analysis/.

Work Cited

"Efi analysis." AssignBuster, 28 Sept. 2022, assignbuster.com/efi-analysis/.

Get in Touch

Please, let us know if you have any ideas on improving Efi analysis, or our service. We will be happy to hear what you think: [email protected]