The main challenges of facility management software are 1) its difficulty keeping up with the pace of technology changes, 2) its fragmented nature, and 3) the poor quality of entered data. Addressing these key issues can help you reap the benefits of the best solutions available today. Here’s how:
Stay In Step With Technology
Everything is moving toward mobile, and many facility management software systems are behind the curve. With billions of internet connected devices operating today, there is no reason for double-work. Because most maintenance technicians are often away from their desks, a modern, mobile technology is usually better suited for your work.
Find a software partner that can easily integrate and update technology changes into a system you’ve already invested in so you can benefit from new developments without a complete system change.
Integrate All Communication Into One
Many CMMS systems are used as an effective collaboration tool for facility managers and maintenance technicians. But, they are often not integrated completely into the daily workflow. That means your team is probably still sending emails, leaving post-it notes, and calling or texting each other. As a result, that communication is not captured, and therefore cannot be referenced, within the CMMS.
By streamlining all communication into one system, you get a complete picture of what’s going on with your equipment. You automatically have complete record of the collaborative effort surrounding a task. From there, it will be easier for managers and administrators to analyze performance of both individual team members and also the team as a whole.
Improve Data Quality Through Training
An obvious benefit of bringing your information into one system is improved quality of information. This must extend to all aspects of your CMMS. During implementation and the early days of a new CMMS, you must train your team to understand and use the system in order for it to continuously collect quality data.
Industry studies show that 70 percent of CMMS implementations fail, and one major factor is poor training. The quality of your entire system rests on the quality of your data - if you put garbage data in, you're going to get garbage data out.
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