Data: Your most overlooked asset

If asked to think of a community’s most important assets, many would likely start by naming road networks, bridges, buildings, or possibly even transit and sanitary systems. But would data ever come to mind?

As the foundation of everything, data is a vital asset—especially for public sector organizations. In order to have confidence in the wide array of operational and strategic initiatives undertaken in any given community, it’s crucial to think of data like you would other assets and consider implementing department standards for data review, quality assurance and quality control practices. Every organization should aim to have access to accurate, reliable and timely incoming data, resulting in data confidence—which should be understood as a dynamic and continuous process.

Establishing a strong data management system guarantees better creation, collection and preparation processes, allowing for optimal data extraction and therefore better-informed decision-making skills. Though this process may seem impossible for those already experiencing time management and capacity issues, attaining data confidence can become a reality for all types of organizations with the proper implementation (and maintenance) of a data management system.

The creation of a data management system
As an integral part of a data management system, implementing a data management strategy is the process of creating a plan to accept the data acquired and how it will be catalogued, managed and processed by an organization.

Identifying the purpose behind your organization’s data collection process will be the first step in developing a data management strategy. Some examples of purposes include those related to asset management, such as wanting to gain maximum value from data assets, while others might be based around goals for financial reporting, work orders, or land planning initiatives. To successfully extract the purpose behind your data, additional supportive data, including static and dynamic data, can help your organization complete the picture of a well-operating data management system.

However, it is essential for an organization to establish parameters for acquiring and structuring all accumulated data well before it is stored. Consolidating data requires a collaborative effort between everyone involved in the data collection process, which is why a centralized data management strategy should allow for the connection of information and data silos, rather than break them down. Once your purpose is clearly identified and the process of acquiring data has been defined, organizations should be equipped with consolidated datasets that are conveniently housed in one system and easily accessible. With a strong data management strategy in place, organizations will not be left to sort through and disentangle scattered datasets that rely on different collection standards and span multiple departments.

Data management system maintenance and data lifecycles
All levels of data should be treated as equals when it comes to data storing and upkeep. Maintaining your entire data collection throughout its lifecycle is equally as imperative to your data management system as it is to the initial acquisition of good, relevant data to your organization. Data lifecycle management follows similar steps to any other valuable asset to your organization.

A simple example to illustrate lifecycle management is that of road maintenance. After constructing a new road, you must maintain the road so it can continue to provide its desired level of service. We maintain our roads by doing things like crack sealing, pothole repairs and resurfacing, and schedule such maintenance on a regular basis to avoid larger, more expensive issues that arise from negligence.

This example is identical to the lifecycle of data. Acquired data requires attention and up-keep to achieve the goal of maintaining reliable, accurate and timely information. Throughout the data lifecycle, data will reach a point where it needs to be evaluated and updated, upon which it can continue to be reused until the next point of evaluation. When your data’s life cycle comes to an end or the data is no longer serving your organization, the data can be archived and new data can be acquired, which should then kickstart the same lifecycle process.

How to know if your organization has data confidence
Data evidently provides a service to your organization, and data also provides a level of service depending on how well your data is structured. The following questions can be used to guide your organization when considering your organization’s state of data confidence:

1. Is your data available to everyone?
2. Is your data complete?
3. Is your data accurate?
4. Is your data updated in a timely manner?
5. Is all of this done with consistency?

To determine whether your organization has strong data confidence, consider these questions to attain a high level of service. It’s important to keep in mind that your data’s level of service may be impacted by various external factors. Some of which include community expectations, legislative requirements, policies and objectives, and resource availability and financial constraints. Additionally, risks to consider while managing your data asset include manual data entry errors, lack of complete information, ambiguous data, duplicate data and data transformation errors. By accounting for these factors, you can maximize your data and strive for higher levels of service for your citizens.

Summary
Good data is a key asset for every organization. The acquisition of continually accurate, reliable and timely incoming information is required for strong data confidence and high levels of service. Identification of data needs, and the development of a dependable data management system is the first step to data maintenance and data upkeep throughout the data lifecycle. Accomplishing true data confidence is a dynamic and continuous process, but it begins with acknowledging the importance of good data and treating your data like a valuable asset to your organization.

Chris Vanderheyden is a director of asset management advisory at PSD Citywide with more than 30 years of combined experience in private and municipal infrastructure planning, design, development and data management. In his role, he leads a team of skilled professionals, overseeing the strategic planning and implementation of asset management initiatives across multiple organizations throughout Canada and the United States. Vanderheyden possesses a degree in GIS and Urban Planning, IAM Certificate, and actively pursuing PMP certification.