How much does each customer cost me?

How much do I really earn?

How many human resources does each customer consume me?

How long have I been with each customer?

What is the difference between theoretical and real time registered by the customer?

What is the difference between the cost forecast and the real cost?

Statistics of real profitability of customers, filtered by:

• Customers (one, several or all)
• Agents and groups (one, several or all)
• Contracts and concepts (one, several or all)
• Tickets including those who are labelled
• Non-labelled tickets (excluding labels)
• Date range (required)

Once filtered, the statistics give us the following data:

• Total number of contracts with rewarded tickets
• Total number of tickets
• Total sales amount of active contracts ((annual amount/365)* number of days of the filter)
• Total ticket time (hours)
• Total cost of tickets (hours* cost/agent hour)
• Difference (total sale amount-total cost of tickets)
• % difference (total sale amount-total cost of tickets)

The list allows us to obtain the following graphs:

• Grouped and individual visibility
• Bar graph, amounts per customer:
  • Sale (contracts)
  • Actual cost
  • Earnings (difference)
• Pie chart:
  • Total customers
  • Total contracts
  • Times used by customer vs. total customers
  • Amount of contract per customer vs. total customers
  • Cost per customer vs. total cost
  • Profit per customer vs. total earnings
• Export of list to graphic (PNG, JPG) and file (Excel, CSV)

What type of contracts do I offer?

How are they grouped together?

What amount do we invoice by type of contract?

How many tickets are related by type of contract?

How much time do we dedicate by type of contract?

What is the cost per type of contract?

How much do we earn per type of contract?

What contracts does each customer have?

Statistics of real profitability of contracts, filtered by:

• Customers (one, several or all)
• Agents and groups (one, several or all)
• Contracts and concepts (one, several or all)
• Tickets including those who are labelled
• Non-labelled tickets (excluding labels)
• Date range (required)

Once filtered, the statistics give us the following data:

• Types of contracts available
• Total customers passed by type of contract
• Total tickets passed by type of contract
• Total time passed by the type of contract
• Proportional cost by type of contract
• Total sales amount by type of contract ((annual amount/365)* number of days of the filter)
• Difference (total sale amount-total cost of tickets)
• % difference (total sale amount-total cost of tickets)

The list allows us to obtain the following graphs:

• Grouped and individual visibility
• Bar graph, amounts per customer:
  • Sale (contracts)
  • Actual cost
  • Earnings (difference)
• Pie chart:
  • Number of tickets by type or contract
  • Time passed by type of contract
  • Sales amount vs. total by type of contract
  • Amount of contract vs. total type of contract
  • Contract cost vs. total cost by type of contract
  • Contract benefit (sale-cost)
• Export of list to graphic (PNG, JPG) and file (Excel, CSV)

A concept of contracts is the grouping of several types of contracts into one.

For example, we have the following contracts for a customer:

• 2 x Virtualization Base Server Agreement
• 2 x SLA-1 commitment Agreement
• 10 x Windows virtualized server contract
• 10 x Windows Open license agreement
• 1 x SLA-II commitment agreement FS server
• 1 x SLA-III commitment contract for other servers
• 8 x SLA-III commitment contract for other servers
• 2x Warranty + Services Extension Contract (HP)

When a technician registers a service, it is very likely that there are several types of contracts that come together (these will include previous contracts). Therefore, we can create two concept of contracts named:

• 2 x Base virtualization servers contract with SLA-I
• 2 x Contract virtualized Windows servers with SLA-II
• 8 x Contract virtualized Windows servers with SLA-III

Regardless of the fees we invoice, both the customer and agents and supervisors will have an easier allocation; for the customers’ account managers, they will have access to customers’ accounts to see in a globalized way the strengths and the weakness  of our relationship with customers.

The same as with the “Contracts” option, but being grouped into “Contract concepts”.

What deviations exist between what I have planned and what is real per customer?

How many actual hours vs. estimated hours have I passed on per customer?

What deviation of hours per customer have I had?

What actual cost vs. estimated cost do I have per customer?

What cost deviation per customer have I had?

Statistics of real profitability of contracts, filtered by:

• Customers (one, several or all)
• Agents and groups (one, several or all)
• Contracts and concepts (one, several or all)
• Tickets including those who are labelled
• Non-labelled tickets (excluding labels)
• Date range (required)

Once filtered, the statistics give us the following data:

• List of active customers
• Number of contracts per customer
• Number of concepts per customer
• Total number of tickets passed by customer
• Estimated time of tickets per customer (hours)
• Total time passed on to tickets (hours)
• Estimated cost of tickets (estimated hours* cost/agent hour)
• Actual cost of tickets (hours* cost/agent hour)
• Cost deviation (real vs. theoretical)

The list allows us to obtain the following graphs:

• Grouped and individual visibility
• Bar graph, amounts per customer:
  • Sale (contracts)
  • Actual cost
  • Earnings (difference)
• Export of list to graphic (PNG, JPG) and file (Excel, CSV)

Which agents are more productive?

Which agents generate the most billable tickets?

What is the workload of the agents?

How many resources do I need to serve my customers?

Real agent profitability statistics, filtered by:

• Customers (one, several or all)
• Agents and groups (one, several or all)
• Contracts and concepts (one, several or all)
• Tickets including those who are labelled
• Non-labelled tickets (excluding labels)
• Date range (required)

Once filtered, the statistics give us the following data:

• List of active agents
• Total recorded time per agent
• Total number of closed tickets per agent
• Total number of billable tickets closed per agent
• Total cost of tickets (hours* cost/agent hour)
• Average cost per ticket (hours* cost/agent hours)

This list allows us to obtain the following graphs:

• Grouped and individual visibility
• Bar graph, by agent
  • Time (hours)
  • Total cost
  • Average cost per ticket
  • Number of closed tickets
• Pie chart:
  • Tickets closed by agent
  • Agent work times
  • Average costs per ticket and agent
• Export of list to graphic (PNG, JPG) and file (Excel, CSV)

Do the agents meet their schedules?

How many tickets is each agent capable of managing?

Which agents close tickets faster?

What is the average time per ticket and agent?

Which agents are the most efficient with their time?

Statistics of work efficiency by agents, filtered by:

• Customers (one, several or all)
• Agents and groups (one, several or all)
• Contracts and concepts (one, several or all)
• Tickets including those who are labelled
• Non-labelled tickets (excluding labels)
• Date range (required)

Once filtered, the statistics give us the following data:

• List of active agents
• Theoretical working time per agent
• Total recorded time per agent
• Total number of closed tickets per agent
• Average work time per ticket and agent
• Minimum working time on ticket per agent
• Maximum working time on ticket per agent

The list allows us to obtain the following graphs:

• Grouped and individual visibility
• Bar graph, by agent
  • Time (hours)
  • Number of closed tickets
• Pie chart:
  • Tickets closed by agent
  • Agent work times
  • Average costs per ticket and agent
• Export of list to graphic (PNG, JPG) and file (Excel, CSV)

What is the most recurrent reason for reopening?

To which agents or groups of agents are the most tickets reopened?

What ratio is there between worked and reopened tickets?

What incidents are most generated in a customer?

What incidents are most generated in an agreement?

Ticket reopening statistics by agent and reason, filtered by:

• Customers (one, several or all)
• Agents and groups (one, several or all)
• Contracts and concepts (one, several or all)
• Tickets including those who are labelled
• Non-labelled tickets (excluding labels)
• Date range (required)

Once filtered, the statistics give us the following data:

• List of active agents
• Reopening reasons
• Number of closed tickets per agent
• Total number of reopened tickets  by reason and agent

The list allows us to obtain the following graphs:

• Grouped and individual visibility
• Bar graph
  • Ratio of closed tickets vs. tickets reopened by agent
  • Reopening ratio per customer
• Pie chart:
  • Tickets closed by agent
  • Tickets reopened by agent
• Export of list to graphic (PNG, JPG) and file (Excel, CSV)

What do my customers value of my company?

How do you rate my satisfaction KPIs (configurable)?

Which agent receives the best and worst rating?

Customer evaluation statistics, filtered by:

• Customers (one, several or all)
• Agents and groups (one, several or all)
• Contracts and concepts (one, several or all)
• Tickets including those who are labelled
• Non-labelled tickets (excluding labels)
• Date range (required)

Once filtered, the statistics give us the following data:

• List of active agents
• Number of closed tickets
• Number of tickets valued

The list allows us to obtain the following graphs:

• Grouped and individual visibility
• Bar graph
  • Ratio of closed tickets vs. valued tickets
  • KPIs chart
• Export of list to graphic (PNG, JPG) and file (Excel, CSV)

What tickets have the agents indicated that are billable?

How do I submit proof of hours spent by email or on paper?

How do I keep monthly control of what I have to bill each customer?

List of billable tickets, filtered by:

• Customers (one, several or all)
• Agents and groups (one, several or all)
• Contracts and concepts (one, several or all)
• Tickets including those who are labelled
• Non-labelled tickets (excluding labels)
• Date range (required)
• Status (one or more) of the ticket

Once filtered, the list give us the following data:

• List of customers with billable tickets by dates
• Number of billable tickets per customer in the range
• Export buttons to PDF, Excel and print

Do I have full control over open and closed tickets?

Can I foresee deviations in the tickets?

How many calls and time do I spend per ticket?

How many e-mails have I sent per ticket?

What tickets have been valued, reopened and which are billable?

Which agents have intervened in a ticket?

Statistics of work efficiency by agents, filtered by:

• Customers (one, several or all)
• Agents and groups (one, several or all)
• Contracts and concepts (one, several or all)
• Tickets including those who are labelled
• Non-labelled tickets (excluding labels)
• Date range (required)
• Status (one or more) of the ticket

Once filtered, the statistics give us the following data:

• List of tickets by state and date
• Customer, subject and ticket status
• Agents who have intervened
• Total time charged to the ticket, by date
• Emails sent and calls made (answered and not answered)
• Time in calls and rest
• Additional Information

Do I have overdue tickets that have breached an SLA?

How long am I breaching the SLA?

Am I breaching the SLA at the time of intervention or resolution?

Do I usually have incidents with SLAs?

Compliance control of agreements subject to SLA, of tickets, filtered by:

• Customers (one, several or all)
• Agents and groups (one, several or all)
• Contracts and concepts (one, several or all)
• Tickets including those who are labelled
• Non-labelled tickets (excluding labels)
• Date range (required)
• Status (one or more) of the ticket

Once filtered, the statistics give us the following data:

• List of tickets according to filters 
• Associated customer, subject and ticket status
• Check control of «late»
• Delay or advance time in intervention (first intervention in the ticket)
• Delay time or advance resolution (ticket closing)
• “NOT APPLICABLE” information when the contract does not include an SLA clause
• Possibility of including SLA clauses in the contract for both intervention and resolution

The list allows us to obtain the following graphs:

• Grouped and individual visibility
• Bar graph
  • Delayed vs. punctual ticket ratio
• Pie chart:
  • Type of delay (by intervention or resolution)
• Export of list to graphic (PNG, JPG) and file (Excel, CSV)

Are my agents fast to serve customers?

Are they attended within a reasonable time?

Are incidents solved in an acceptable time?

Statistical compliance with punctuality standard, filtered by:

• Clients (one, several or all)
• Agents and groups (one, several or all)
• Contracts and concepts (one, several or all)
• Tickets that include certain labels
• Tickets do not include certain labels (excluding labels)
• Date range (required)
• Status (one or more) of the ticket

Once filtered, the statistics give us the following data:

• Customers 
• Current ticket status
• Check control of «delayed»
• Intervention time 
• Resolution time
• Time colors (red / green) to indicate if global Quality or Services parameters are met (company configuration)

The list allows us to obtain the following graphs:

• Grouped and individual visibility
• Bar graph of  average intervention times and resolution by number of tickets
• Export of list to graphic (PNG, JPG) and file (Excel, CSV)