Workplace observations contribute crucial worker insights

Context

After implementing a new management operating system and framework, our client, a prominent coal seam gas provider, faced a challenge in assessing its progress. While the business had access to extensive data on production and asset performance, it lacked valuable insights into workforce productivity, the impact of changes on employees, and how well the employees were adapting to the new system.

By placing people in the centre of the solution, Minset knew it could collect meaningful data directly ‘from the field’. This data would help bridge the client’s information gaps, enabling it to evaluate levels of productivity enabling the organisation’s ongoing change and business improvement agenda.

Approach

The Minset team:

• Strategically assessed the workforce and created a plan to collect data across various business units and roles – from control room operators to maintenance technicians and contractors.
• Used two types of observation strategies to measure productivity. For leadership and technical roles, the team conducted DILO (Day in the Life Observations) to understand the balance between high-value work and administrative tasks. For operations and maintenance roles, we used ‘Tool time’ (also known as wrench time) to measure productivity rates and evaluate the time spent on specific tasks.
• Utilised a mix of verbal questions and workplace observations to pinpoint discrepancies between what was actually being done in the field and the approved procedures.
• Spent an entire shift interacting with each team on the ground, discovering workplace challenges that were previously unreported. These included ripple effects caused by vacant positions and the negative consequences of using complicated systems and processes.
• Used its proprietary tool time app, MinObs, to build a fast, accurate, and data-driven picture of work performance. Observations were categorised using Lean methodology time categories.
• Created a reliable and repeatable measurement methodology to gather and produce data now and in the future.