According to a recent Deloitte survey, the most difficult part of any leader’s job is wading through a mountain of productivity data. As a result, it should come as no surprise that businesses invest in workforce analytics intelligence software to successfully manage and support their employees’ productivity. However, in doing so, data collection and maintenance are becoming a formidable challenge – even for large, successful companies.
The increased use of workforce analytics represents a shift in how businesses use data to make better productivity decisions and improve employee performance.
This article will cover everything you need to know about data-driven advances in workforce analytics, so that your team can get the most out of employee data and elevate your company’s productivity.
What Are Advanced Workforce Analytics and Why Do They Matter?
Advanced workforce analytics is the concept of utilizing enriched workforce productivity data and applying a scientific methodology to measure, optimize, and improve workforce productivity within an organization for better business outcomes.
By applying this approach, managers and people leaders can make more informed decisions that positively impact their overall performance, uncovering areas of improvement to promote workplace synergy that brings about positive change.
When it comes to workforce productivity analytics, there are a few terms that play a critical role in determining the success factor of any business:
- Workforce Productivity Analytics examines employees in the workplace by analyzing how effectively work is done to improve productivity and streamline business processes. This includes morale gauged through methods such as differentiating and analyzing active time versus inactive or unproductive time.
- Descriptive Analytics is the most basic type of workforce analytics you’re probably familiar with. It is the summarization of historical workforce data into something understandable. A headcount of all employees within the organization is a descriptive analytic that can be viewed over a large time period. To further dive into the matter, you can segment all your employees by department or project, which would result in the same overall conclusion.
- Predictive Workforce Analytics looks forward to answer the question as to what might happen in the future within an organization using statistical models and forecasts. Analytical models are based on patterns discovered in descriptive analytics. The goal here is to proactively identify your organization’s needs in the future.
- Prescriptive Workforce Analytics provide recommendations on what to do based on predictions and past events. This analytical approach can be extremely useful for organizations that have peaks or busy seasons. Let’s say you’re a call center that needs to ramp up its workforce during the holiday season. Using prescriptive workforce analytics, you can accurately predict the number of employees you will need or the hours that could be potentially billed. Another use case is for outsourcing IT firms. You can look at previous data for similar or related projects thus accurately predicting the number of employees you will need for a particular project. This can also help you give more accurate quotes for certain projects by looking at past data.
What Are the Benefits of Advance Workplace Analytics
Workforce analytics offer numerous advantages to organizations of all sizes and stages of development.
Its main advantage is that advanced workforce analytics reduce the amount of guesswork in workforce planning and management by identifying data-driven ways to optimize processes. Companies can confidently make decisions based on a solid foundation of data science, from identifying optimal productivity to analyzing time and attendance patterns.
Companies, however, often struggle with the collection and maintenance of the massive amounts of data required for effective workforce analytics. As the digital world scales from in-house data interactions to a network of data exchanges to achieve the desired success, at Insightful we are following the trend by offering our users the ability to export workforce analytics data through our Data Warehouse Integration.
Accurately Identify Gaps to Increase Productivity
Companies frequently rely on manager feedback to learn about various skill gaps within the organization that are affecting productivity. However, because this relies on managers to accurately assess the most critical needs, this approach frequently leads to human error and biased decision-making.
An employee tracking system like Insightful offers workforce analytics to identify where your workforce skills do not align with the skills required for core responsibilities and use this information to remove bottlenecks and increase overall productivity.
Companies can reduce unnecessary distractions, reduce bottlenecks, and remove roadblocks that prevent employees from reaching peak performance by gaining a deeper understanding of the efficiency of day-to-day operations.
Improve Employee Retention and Prevent Employee Burnout
Workforce analytics assist in the development of employee experience practices that result in higher job satisfaction and retention among your employees.
Companies can find data-driven insights to improve employee morale and loyalty, leading to higher productivity, by getting a complete picture of employee behavior and performance using a mix of operational, historical, and internal data.
By clearly understanding what causes employee burnout and fatigue, business leaders can modify workflow structure to significantly reduce employee turnover.
Insightful BigQuery Data Warehouse Integration
Multiple data systems that cannot be easily linked with unique identifiers will make any workforce analytics process time-consuming. Without a full-time workforce analytics analyst, managers and people leaders may not have the time or the expertise to devote to higher-level analytics.
However, systems and workforce data automation can be beneficial as they can generate reports automatically, and workforce analytics software like Insightful makes it even easier.
BigQuery integration makes it easy to load Insightful data into a BigQuery data warehouse. When you integrate BigQuery with Insightful, you get a fully managed data pipeline loaded into a powerful and cost-effective data warehouse.
Insightful runs a periodic process to pull data related to your organization, teams, and employees from our database and load them into your BigQuery cluster.
To learn more about BigQuery Data Warehouse Integration check out our knowledge base article.