Proactivity in IT
Updated: Sep 1
Written by David Lareau
In my last article I spoke about left shift during development process. This principle means that tasks performed upstream are more efficient, more profitable than when they are done in reaction. The same shift left principle applies to support: allow level 1 teams to resolve incidents that are usually resolved by higher level of support, reduce costs by improving documentation, enable self-service tools, scripts, automation, training, auto-healing and proactivity in general.
It is known that the cost of a support ticket opened at level 1 (helpdesk), which then passes to level 2 and settles at level 3 is much more expensive than a ticket settled using a self-service tool (commonly called level 0). Now, imagine an investment in prevention (level -1) to ensure that the incident ticket is avoided. A dollar invested in prevention is inversely proportional to the profit it generates.
The efforts to act proactively in IT must be put into:
Improving processes such as change management to prevent incidents.
Problem management in order to manage the unknown source of multiple incidents.
Analyzing the source cause (RCA) of major incidents to learn from past errors and fix whatever needs to be fixed in order to prevent incidents from happening again
Setting routines, creating recurring meetings in your calendar (yes, routine can be captivating!), weekly CAB, quarterly review of customer contacts, monthly review of action point progress
Only what is measured can be improved, measuring the right indicators is critical. Monthly review of key indicators (KPIs) of availability, ticket processing capacity (number of opened tickets subtracted to closed tickets), customer satisfaction, FCR
First call resolution rate (demonstrate the effectiveness of the Level 1 barrier proving that the Dev, Infra, catalog, etc. teams are freed from unnecessary workload)
Team billable hours in tickets (show profitability: the time is spent on customer tickets vs administrative tasks, meetings, etc.)
Overtime charged (effectiveness of alerting, auto-healing, scripting, system stability, profitability)
Profitability per customer (number of hours worked in tickets / monthly price paid for support)
Number of pending tickets per client, average ticket age per client (verify if there is any capacity issue or blocking Level 1 teams)
Number of tickets per assigned teams (which level 1 teams are blocking)
Number of closed-opened tickets (compare month-to-month occupancy rate, a deficit shows a capacity problem)
Integrate routines (weekly, monthly) make ritual follow-ups
Quarterly customer review: contacts notification, escalade monitoring
Internal quarterly review: major incident process, profitability measurement (billed vs worked), backlog, problems, incidents without a follow-up.