Your team is hesitant about proactive maintenance planning. How can you convince them using data analytics?

One time at work, my team was skeptical about proactive maintenance. In my experience, using data analytics made a huge difference. By analyzing past maintenance records, we could predict equipment failures and schedule repairs during off-peak times. One thing I found helpful was showing how this approach reduced downtime and increased equipment uptime with clear charts and real-world examples. This data-driven method convinced the team of the benefits, making the case for proactive maintenance much stronger.

Before using data analysis, make sure you have the necessary and sufficient tools to process the data you consider relevant. Before knowing which tools to use, make sure you know which data is relevant. Once you know these two things, then proceed to data analysis, but ensure that you choose the necessary and sufficient tool to process the data. Untreated data is just accumulated information that doesn’t create value; on the contrary, it represents a cost that someone has to bear

"Convincing my team about proactive maintenance? Leverage data analytics! Show them how predictive insights can reduce downtime, cut costs, and extend equipment life. Data-driven decisions not only prevent failures but also optimize operational efficiency, turning maintenance from a reactive expense into a strategic advantage."

Melhorar a Confiabilidade e Disponibilidade do Equipamento • Tempo Médio Entre Falhas (MTBF): Mostre como a manutenção proativa pode aumentar o MTBF, indicando uma maior confiabilidade e menos interrupções inesperadas. • Análise de Disponibilidade: Use dados para demonstrar como a manutenção proativa pode melhorar a disponibilidade dos equipamentos, resultando em uma operação mais estável e previsível. Aumentar a Eficiência Operacional • Benchmarking: Compare os dados operacionais de antes e depois da implementação de práticas de manutenção proativa em equipamentos semelhantes em outras instalações ou empresas.

Fleet delivery teams are often compensated on making deliveries ($ / stop, $ / piece, $ / mile). Keeping the fleet up and running is critical to not only company success, but driver take home pay. I recommend using solutions with IoT predictive analytics with embedded managed AI services. Watch and fix for issues before they start to mitigate downtime!