This piece will touch on the importance of having the right data and using it correctly. It will give tips on data quality and how to ensure data is meaningful.
To enable accurate capital planning and facilities management, Facilities Managers must rethink data standards and ensure they are capturing the right data. Today’s devices and smart systems generate more data on a daily basis than in the entire sum of data generated throughout the course of human history. As explained by Greg Cline of Business2Community, the entire facilities management industry is pushing to add value through data, with up to 40 percent seeking to improve visibility. An additional 50 percent are looking to leverage third-party partnerships, and up to 37 percent seeking to establish facility-wide visibility of assets and synchronize performance capacity with corporate goals. Therefore, understanding how data quality matters for proper capital planning and facilities management must be a top priority for Facilities Managers.
Poor Data Leads to Poor Capital Planning
Take a moment to think about what goes into capital planning for facilities. Facilities Managers must consider first work maintenance needs, projections of reactive maintenance, asset replacement, and more. Since controlling costs, including energy costs, outsourced services, and maintenance costs, forms the spear of capital planning, leveraging data for these purposes must take priority over all other needs, explains Bryan Christiansen of Buildings.com. Essentially, poor data quality will lead to inaccurate capital planning in facilities management.
Data Quality Is Key to Accurate Capital Planning in Facilities
Better data quality is associated with improvement of facilities management outcomes and asset management. According to Phil Wales of FacilitiesNet, traditional maintenance schedules have been the primary source for routine maintenance needs, such as changing filters and replenishing HVAC system collects. Unfortunately, this structured form of maintenance may not necessarily be appropriate for each facility.
For example, facilities in climates with access to pollutants or additional dust in the air will require more frequent maintenance schedules for the HVAC system. In addition, the HVAC system may malfunction, or other problems may arise. Traditional approaches are not optimized, but Facilities Managers that have reliable data quality can refine maintenance schedules and transition from a reactive to proactive maintenance and facilities management strategy. Meanwhile, smart sensors, connected to the facilities management platform can verify asset function and ensure the timely completion of all necessary repairs, minimizing disruptions along the way and adding brand value.
How to Verify Data Quality for Real-World Use
Maintaining the validity and verifying data quality is not as simple as it sounds. Facilities Managers can look at a data set, and it is almost impossible to determine if the data is accurate or inaccurate. Obvious problems may exist, and be noticeable, but the granular level of today’s data in modern facilities management makes it impossible to recognize data problems with the naked eye. As a result, Facilities Managers should take steps to ensure data quality is superior and proper quality. These include:
- Retrofit the facility.
- Make data easily accessible and able to be used appropriately.
- Collect the right data.
- Act on data.
- Follow through on data results and improvements.
- Repeat the process.
Leverage Data Quality-Based Capital Planning With a Smart Building Solutions Now
Achieving accurate capital planning and facilities goes back to having an accurate account of facility assets and understanding the granular needs of a facility. Facilities Managers must retrofit their facilities, follow the aforementioned steps, and continue to improve on existing management and maintenance practices. Due to this level of complexity, outsourcing may be the solution for your organization. Visit ENTOUCH online to learn more, or give us a call at 1-800-820-3511 today.