Contractor Job and SLA Management

Home

Aquaheat is an NZ based HVAC / mechanical services contractor. They are an industry leader in this space operating in New Zealand and Fiji.

Managing over 1000 contractors, SLA's and a wide range of jobs, Aquaheat's operations team was spending hours trying to manipulate data in excel and creating ad hoc reporting resulting in missed SLAs & inefficiencies.

During the initial discussion with the operations manager, it was quite clear that the business has been growing which created more work for the admin team in terms of job logging, reporting, etc.

While they have been completing these tasks manually before it was imminent it was getting out of hand. Another key issue highlighted was "we spend too much time manipulating data and not enough time to understand what's happening".

Solution

Our immediate goal, while working on the solution was to have an efficient data prep model which would collect, clean, and store the data in a structured format without much effort. Used Cloud and Power Query.
After achieving the first goal we then delivered a Power BI Reporting solution allowing the business to step into its next phase of growth.

Outcomes

Interactive Power BI dashboards enabled the operations team to spend more time consuming the data. This allowed the team in becoming more proactive than reactive
Automated data flows meant no time was spent anymore manipulating data.
With a reliable and scalable solution, the business was able to spend more time exploring different ideas, testing them with relative ease, and becoming data-driven

Solution

Our immediate goal, while working on the solution was to have an efficient data prep model which would collect, clean, and store the data in a structured format without much effort. Used Cloud and Power Query.After achieving the first goal we then delivered a Power BI Reporting solution allowing the business to step into its next phase of growth.

Outcomes

Interactive Power BI dashboards enabled the operations team to spend more time consuming the data. This allowed the team in becoming more proactive than reactive Automated data flows meant no time was spent anymore manipulating data. With a reliable and scalable solution, the business was able to spend more time exploring different ideas, testing them with relative ease, and becoming data-driven