Back to all posts
Masooma Memon

Quality Data & Resource Management: A Match Made in Heaven

You can't do effective resource management based on vibes alone. High quality data unlocks the true potential of resource management: let us explain how.

There’s no getting away from it: strategic, effective resource management depends heavily on data. 

In fact, we’re going to go out on a limb and say that poor data governance is often the biggest factor that limits businesses from doing more with their resource management.

Practices like capacity planning and workforce development require high-quality, consistent data from across various business units — empowering resource managers to identify patterns in performance and use data to make informed decisions. 

But if there's no process for standardizing resource data in your organization, where do you even start? And how could you be using your data more effectively? We’ve got all the answers for you below. Dig in. 

Why data is important to resource management

Data doesn’t have the whole story, but the data does give answers and directions for where you should be looking, or where you should be maybe prioritizing or rethinking some of the allocations or priorities that you have” - Laura Dean Smith, Director of Consulting Operations (Resource Management) at Clarivate

Good quality, standardized data is key to unlocking the full benefits of effectively managing project resources and scaling resource management as a function.

In fact, it’s critical for leveling up what resource management can achieve for the organization — from giving the business a competitive edge to engaging (and better retaining) employees.

Here’s a quick rundown of the importance of consistent, well-organized, and maintained data:

  • Efficient resource optimization. Data gives resource managers actionable insights into inefficiencies in resource utilization, allowing for optimal utilization and capacity planning
  • Informed decision-making. Consistent data gives visibility into resource availability and patterns in employee utilization, performance, and demand — allowing you to strategically plan and manage resources.
  • Project deployment success. Efficient data governance enables teams to improve the quality of project deliverables. This is possible thanks to using data to allocate the right resources with the most relevant skills and availability to upcoming projects. Not only does this guarantee project success but ensures timely delivery as well.  
  • Effective risk management. A high-quality data stream into performance helps to quickly identify project risks and bottlenecks before it’s too late. For instance, you can review resource availability data to see which employees have booked vacation during the course of a project. Using the data, you can then coordinate timelines to assign other folks to the project, preventing any project delays that happen due to finding last-minute replacements.
  • Stakeholder engagement. Data availability helps you update all internal and external stakeholders on project progress and performance in a timely manner. In turn, this fosters trust. What’s more, data on utilization rates can help you better engage — even get buy-in — from the C-suite. 
  • Better resource planning and forecasting. By analyzing patterns in your data, you can also anticipate future resource needs and plan accordingly. In fact, analyzing skills data empowers resource managers to invest in strategic skills development that helps organizations keep up with the changing work landscape.
  • Maximize resource efficiency. Continuously monitoring resource data allows managers to determine how management strategies are doing, identify opportunities for improvement, and track progress.

Admittedly though, these benefits of data in resource management are only the tip of the iceberg. Because as you’ll learn in the next section, savvy resource managers who have a defined data governance strategy in place use data to improve employee engagement as well.

Since engaged employees are less likely to quit, data contributes to helping them retain better.

Additionally, consistent data analysis in resource management also gives organizations a competitive edge. This comes off the back of improved operational agility, boost in client satisfaction, and cost savings in resource management and employee retention.

Not to mention, thoughtful employee skill development helps companies achieve their goals. 

How do resource managers use data?

Data is really your best friend. If you have a PSA tool, going through and seeing that you’re able to run reports — for instance, seeing all of the past projects that have been done for the same client — who and what are the common resource names and roles that you’re seeing? Are there commonalities and project names, information you can pull out and use to inform your decisions?” - Laura Dean Smith

From using data to plan, manage, and schedule resources to leveraging it for boosting employee satisfaction and getting stakeholder buy-in, there are tons of ways resource managers use data. 

Let’s look at these use cases one by one: 

Data for unlocking maximum project success 

Data helps in a handful of ways here. 

For one, it provides visibility into resource availability, skillset, and the times employees are due an off. This allows managers to select the right people for open and future projects. It also ensures these people are available to work on the project for the entirety of its duration.

Two, reviewing past data into projects shows resource managers common themes into the people who worked on them, their performance, and similar. In turn, the information can help you make informed decisions to improve the quality of deliverables.

Lastly, data also lets you identify patterns in demand. For example, if a certain supplementary service has been helping some clients, you can cross-sell it to other clients.

A thorough data review can also assist you in seeing upcoming challenges such as gaps in the work pipeline — allowing you to proactively dissolve those challenges before they grow to become a problem. 

Data to skyrocket client satisfaction

An essential aspect of client relationship management is sharing timely progress updates. These would, however, be time-consuming if you don’t have consistent data.

With a standardized data governance policy, you can quickly share precise progress and performance updates with clients.

The same data also assists resource managers in evaluating project performance — identifying areas for improvement and opportunities for optimization. 

Data for securing stakeholder buy-in

Resource managers also use high-quality, consistent utilization metrics to get stakeholder buy-in. When pitching the value of resource management to any interested parties, having this data on hand helps to make your case watertight.

In our guide on getting stakeholder buy-in, Gary Ward, the Director of Global Resource Staffing at Guidewire, recommended looking at the data you may already be tracking (think: time tracking data from timesheets) as the place to start when making a case for investment in software that will surface more detailed resource management data. 

Data for strategic resource allocation and workforce development

Yet another way resource managers leverage data is by making a skills inventory that features all employees’ skills, experience, and interests.

Made in collaboration with individuals, a filterable skills inventory is a quick and efficient asset for assigning work to people with the relevant skills.

For example, if you’re looking for people with a specific skill for a new project, you can type in the skill and search for the right people with the availability:

Besides effective resource allocation, you can use the same data for a skills gap analysis.

Essentially, this analysis is a technique to identify what skills your current workforce has and what critical skills the business needs from its employees.

A thorough skills gap analysis helps both the organization and the workforce by:

  • Readying the workforce with the essential skills the business needs to stay ahead of the curve
  • Investing in employees’ professional development which, in turn, keeps them engaged since 87% of millennials and 69% of non-millennials say learning and development opportunities are essential to them in a job.

Data for employee engagement, satisfaction, and retention

The role that data plays in allocating resources and skills development also contributes to engaging employees at work.

For example, when you assign individuals to projects that match their skills and interests, you end up giving them meaningful work that challenges and engages them.

By ensuring you allot work based on employees’ availability and to the optimal of their capacity, you can further improve employee satisfaction. This happens as your data pool shows you which employees are due an off, who have plates full of work, and which ones can take on more tasks. 

In turn, this systematic, data-informed approach to resource allocation keeps workforce burnout at bay.

Not to mention, by giving individuals opportunities to learn and develop new skills, you can increase the chances of retaining them better.

Further reading ➡️ The Ultimate Guide to Employee Retention Strategies.

Data for accurate forecasting and capacity planning

Last but not the least, by diving into past project data, resource managers identify patterns in resource demand.

Say, for instance, the demand for your products/services grows in the winter. With data to confirm this hypothesis, businesses can accurately forecast the need and plan for resources accordingly.

Accurate, consistent, standardized: how to make your data useful

Data in resource management is only as useful as its quality.

Data quality, however, is determined by your data collection, standardization, and maintenance processes — altogether referred to as data governance.

 Most organizations don’t leverage resource management data to its best potential. Two prominent reasons for this include:

  • Lack of proper data governance or a set team responsible for it
  • Lack of or incorrect deployment of the resource management software  

Meaning: the most effective way to make your data useful is by building the following strong pillars:

Standardize data with a data governance strategy

You really should have one set of best practices, one set of processes, one set of reports, one set of metrics that you can use across all the different areas. If you’re doing something for one group, then you really need to think, should I be doing this for all of the groups? And if the answer is no, then you need to ask yourself, then why am I doing it for this group?” - Laura Dean Smith

A data governance strategy defines your data collection and maintenance processes - it's a consistent set of best practices you follow to ensure that the data you need is always clean and fit for purpose.

Put this way, you’ll see that a governance strategy aims to build a standard policy for the metrics to gather and measure. Your strategy should address the following questions:

  • Who is responsible for collecting data?
  • Who is responsible for maintaining the data?
  • What metrics will you use to measure different resource management aspects?
  • What tools will you use to gather and maintain all these metrics? 

Use a robust resource management software

A powerful resource management software serves as a single source of truth where data is accessible to all those granted permission.

A central platform also prevents duplication of efforts and confusion around data entry. It allows for data integration with other platforms as well — making it easy for you to actually leverage the data for decision-making.

However, having a resource management solution is not enough. You need to also make sure it’s implemented correctly so there are no process bottlenecks such as data inconsistencies.

The best part? When you choose a resource management software (like Runn 👋) you can use it to collect and analyze data with its powerful reports, resource scheduling, and capacity management

Have a change management plan in place

Implementing a standardized, consistent data governance strategy means people have to go beyond the status quo. Naturally, this creates resistance to change as folks have to do things differently.

For successful implementation, it is imperative you have an action plan to counter this resistance to change.

One effective way to do so is to frame the benefits of each department’s goals. This means when you lay out the plan, you don’t go on and on to explain the business benefits of standardizing resource management data.

Instead, explain how collecting consistent data will benefit each team ✅

For example, if a team has been raising concerns about their workload exceeding their capacity, tell them how data consistency will help them with capacity planning and help them make a compelling case for new hires. 

Next steps: Getting started with data cleanliness 

Data in resource management plays a vital role in different aspects of planning, managing, scheduling, and optimizing employees. 

But the only way to squeeze value from the data you’re collecting is to set standards for it. 

Determine which metrics teams should be measuring. Assign data maintenance responsibility to team leaders. Highlight and train teams on using the gathered data to monitor performance and make informed decisions. 

Most importantly, use a central resource management space to track and analyze all the data. 

Looking for an easy-to-use solution? Request a demo of our powerful resource management platform and our team will take you through how Runn helps manage data, or start a free trial to take a look for yourself.

Enjoy the post? Sign up for the latest strategies, stories and product updates.

You might also like

Try Runn today for free!

Join over 10k users worldwide.
Start scheduling in less than 10 minutes.
No credit card needed