This article discusses how customers can take advantage of Field Pro software to set and measure their business goals over a period of time. 

I - The formulation of the objective

A business objective generally meets two types of needs:

  1. Controlling the performance (of its salespeople, its teams, its products)

  2. Motivating and rewarding employees or business partners

Several elements must be taken into account when formulating it: 

  • What is the action to measure?

  1. Adoption of the web application: the number of active users, % of connection, % OTP Requested, the number of licensed users...

  2. Commercial activity: the number of visits, the time spent during a visit, the conversion rate per visit, the coverage rate of the customer portfolio, the number of orders, the turnover per order...

  3. Completion of tasks: the number of tasks completed...

  4. Product performance: the number of products present, the level of stocks...

  • What is the element concerned? 

A user, a team, a product category, a customer, a task.

  • What is the measurable result to be achieved? 

  • How long does it take to accomplish the goal?

Several examples of clients' objectives:

  • A user must visit at least 5 points of sale per day.

  • A team must place orders for a minimum amount of $ 500 per month.

  • A product line must achieve a minimum attendance rate of 75% per week. 

  • At the end of the quarter, the task category “Retrieving an administrative document” must reach a completion level of 100%.

II - Setting up the objective on Field Pro

To set up your business goal, the operations team needs the following elements : 

  1. Frequency of completion





Update based on frequency

Yes : a different update for each time period

No : the same target no matter the frequency

2. Scope of the target

A mobile user, a team

An attribute based on a list (a product, a place, a task...)

3. Type of target

Based on list

Based on historical data


To create : A list with

  1. Mapping field (=user_id or item_id) according to the scope
    2.Target value

  2. Indication of the time covered by the target if the target needs to be updated for each time period.
    If month > single choice September, October,...
    If week > NB of the week
    If day > Date

To provide :

an example of calculation

4. Reward



If Reward

Based on a calculation

Based on a reward grid


To provide :

An example of calculation

A list needs to be created with :
1.Condition for each reward level
2.Value for each reward level

5. Access




To provide : a list with the web users who can access the dashboard

III - The measure of objective completion

The measure of goal completion is often calculated as a percentage comparing the achievements with the forecasts.

Completion of the objective: 100 * (Achievement / Forecast)

  • If the completion is less than 100: the objective has not been fulfilled.

  • If the completion is greater than or equal to 100: the objective has been fulfilled.


Initial objective : 15 weekly visits per user. Achievements: 12 weekly visits per user. 

% of goal completion: 12/15 * 100 = 80%.

IV - The visualisation of objective completion on the WebApp

Three graphic components allow to quickly understand the goal completion. 

1. The gauge chart

Displays how an actual level of performance operates in comparison to the budgeted.

Best use cases - aggregation of the objective to a set of elements (% of active users, % of point of sale coverage,% of completion of a given task).

2. The table 

Displays a grid that contains related data in a logical series of rows and columns.

Best use cases - detailed view of the completion of the objective at an individual level : a user, a team or a point of sale (% of target visit completion, % of orders made compared to forecasted). 

3. The matrix table 

A table collapsed and expanded by rows and columns.

Best use cases - detailed view of the completion of the objective at an individual level : a user, a team or a point of sale (% of target visit completion, % of orders made compared to forecasted).