Understanding data driven facilities planning

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Real-time access to accurate facilities data enables facilities teams to instantly understand the status of their buildings space and equipment across their portfolio. This empowers them to quickly answer questions with considerable confidence especially when businesses need to remain agile at times when their effectiveness is most vulnerable. An accurate inventory of facilities space and assets can help organizations to better plan for long, medium and short term planning horizons. Examples of each are as follows:

Long-term

Being able to utilize accurate existing information and plan for long-term growth or contraction of a facilities portfolio is critical for understanding the costs and implications of major capital plans which often extend several years into the future. Maintenance Dashboard
Planning for new facilities that correctly meet the evolving needs of an organization involves understanding the current state of a facilities portfolio and how it’s changing.  Applying analytics to inaccurate data which is used to project future facility needs can lead to massive costing errors when facilities are over-built, under-built or built without a realistic understanding of the needs of future occupants. This can lead to unnecessary spending and reduced employee satisfaction and productivity due to facilities being constructed that don’t meet a business’s needs.

Medium-term

Medium-term planning can involve making decisions about your buildings in a 1-3 year time frame and typically will include smaller less significant changes than would be seen in major capital projects. This can involve expansions and contractions including changes in an organizations leased space as well as major and minor moves within an organizations existing facilities portfolio. Over leasing space because a facilities team doesn’t have an accurate picture of occupancy vs. utilization is a common mistake that organizations make when they don’t have up to date physical space inventory. Accurate facilities data goes well beyond understanding how much space an organization has and how it is classified for effective medium-term facilities planning. Additional items that organizations need to understand are critical dates such as rent bumps, leased space end dates and renewals as well as how effectively existing own space is actual being utilized. Facilities teams for instance will often report that their portfolio is almost fully occupied when in reality utilization is quite low as alternative workplace methods and technology changes are enabling employees to be out of the office and working remotely more often than ever.

Short-term

Short-term planning is typically utilized to help manage unexpected changes that occur that a facilities organization was not able to predict with either medium or long range planning. There are two basic types of short-term plans and both require an up to data and accurate facilities inventory which includes conditions. The first type are usually reactive and are created in an ad-hoc manner and can involve events such as unplanned mergers and acquisitions, tactical restructuring to quickly build teams of employees for new business challenges or minor facilities problems such as building system failures that happen unexpectedly and require employees or assets to be moved. The second type are short-term plans that typically “sit on the shelf” ready to be acted upon when more severe changes occur to an organizations facilities such as an environmental disaster which can result in either the temporary or permanent loss of a facility. The implications of not having an accurate facilities view for events such as this can cause numerous problems such as not having a complete picture of what is inside of your facilities that can be provided to rescue personnel during rescue and recovery options. It can also lead to financial repercussions as well when an organization cannot effectively report on their assets for insurance purposes to help them obtain the necessary funds for recovery.

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