Graph shows pillars of information management: People, process, technology, content
3 practices to ensure your property data is in good shape

Since property asset managers deal with numerous data types and data entries daily, compromised data – whether data is outdated, missing, inconsistent or contain errors – becomes a common problem faced by many. This problem is not unique to real estate property management but is a general issue in information management. Considering the pillars of information management: people – process – technology – content, there are three practices you can apply to improve quality of your property data.

  1. Create a process for data maintenance

One of the main causes for data problems is often the way data is recorded and stored, particularly in property asset management when data comes from different sources internally and externally. A simple solution here is to have a standardised business process in place with conventions and rules to guide your data maintenance routine. Make sure to cover several key elements in this process

  • What is the essential data for your practices
  • How to input information correctly for each data field
  • How often the data should be updated
  • Who is responsible for each data maintenance task
  • How to review data quality and check for data errors

Let’s consider managing your basic property information, do you have a timeline to verify square footages of all properties? Or is there a convention on how property address should be recorded (to avoid variation e.g. Hämeentie 10 A, 00101 Helsinki, Finland or Hämeentie 10 A, Helsinki 00101, Finland)? Guidelines for such practices might seem trivial, but collectively they define the shape of your data.

2. Get your team onboard

Even the most perfect process is useless without it being practised. Hence communicating the data maintenance standards and encouraging your team to comply is an important next step. Think of your team in this context as everyone involved in managing your asset including external personnel. To get your team on board consider offering:

  • Training on process and standards for data entry
  • Reward for team members with high-quality data

Systematic training is great to establish standardisation in your operation. Organising training for all people involved in your entire portfolio at once might be overwhelming, but you can take a step by step approach, e.g. start with facility managers then proceed with lease-hold managers, risk managers, etc. Take time to make sure everyone understand and are able to implement the conventions accurately. In order for the process to uphold in a long run, it is necessary to enforce the best practices using recognition and rewards. Don’t hesitate to compliment and offer bonus to your property managers for their data-maintenance efforts!

3. Assess data quality regularly

Let’s say you have a process in place which your team follows strictly, you can still face data problems due to human errors. Some mistakes can be spotted easily while others can be lost in a mist of information chaos, hence monitoring your database regularly is needed for consistent high-quality data. Whether you have a simple document storage or advanced property management system(s), having defined method to assess data quality will result in major improvement in data’s overall condition. This is especially true when dealing with multiple information sources in which cross-checking between sources is imperative.

Data assessment can be done either according to predetermined schedule or as random inspection. Since the task can be complex and require thorough understanding of your property data structure, having a data expert or dedicated team member to monitor and correct your data regularly is certainly more effective than holding semi-annual or annual reviews.

Maintaining data, for any organisation, is an investment that will yield short and long-term benefits. For property asset management, well-maintained data helps you stay current and eliminate hidden risks in your portfolio.