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Business Intelligence Solutions for a Remote Workforce

As businesses adapt to a remote workforce amid the global COVID-19 pandemic, they will continue to turn to data analytics to ensure operations are optimized. It’s how productive, not how much your employees work, that matters. Sometimes quality is more valuable than quantity. Raw data, alone, doesn’t tell you anything. Only when employee data is integrated with operational data will you have a complete view of overall employee productivity.

Applying a Framework for Analysis

Business intelligence (BI) for a remote workforce is no different from BI for a traditional workforce; it just requires other measuring tools. Like any other project, it’s essential to understand what you’re trying to build before acquiring new tools. With the dramatic and immediate switch to a work-from-home structure for many companies, tools abound that provide analytics, but what you really need to understand the analytics is a technology-driven process for analyzing data and delivering actionable information that helps all executives, managers, and workers, make informed business decisions.

Business intelligence includes comprehensive metrics to support better decision making at every level of the organization. Analytics alone may tell you that hours worked, for example, are down - but unless shown in the broader context of business operations, you may be using the wrong tools.

Employing business intelligence for remote employees means much more than tracking time. You can only get a 360-degree view of employee productivity by bringing together all the relevant data under one roof to get an accurate measure of performance. This article will demonstrate how to do this by viewing the “remote employee problem” inside a systematic framework for analysis, which includes:

  1. Understanding the Problem

  2. Understanding the Data

  3. Preparing the Data

  4. Modeling the Results

  5. Evaluating the Findings

  6. Deploying a Solution

1. Understand the Problem

Businesses are concerned with how much their employees are working from home. As if there was no way to procrastinate while in the office? So they implement time or activity-tracking software. Time-tracking is good, but how much is not the problem. How productive is more accurate. A complete look at the problem might be: “how productively are my employees using their time?”

2. Understand the Data Sources

Now that we understand what we want to measure, we need to understand the data sources available. We’ve already mentioned time and activity tracking, but they just tell you how much or what your employees are spending their time doing. To get a full understanding of productivity, we need to overlay time and activity with production data such as sales, projects, and transactions.

3. Prepare Your Data

Once you have identified the data sources housing the data needed, the next step is to get all of the data under one roof. The raw data needs to be cleaned and scrubbed and then integrated to form new attributes and classifications. For example, you will want to classify hours worked as either productive or non-productive by correlating employee time and activity metrics with known business profit and loss attributes.

4. Model the Results

The next step is to model and visualize the combined data to derive insights. Modeling may include applying algorithms and mathematical expressions to help your team focus on business improvements. Visualization will aid in the understanding and analysis of the results so that stakeholders can take action.

5. Evaluate the Findings

With multiple data sources integrated, the data sets correlated, and the results presented, the next step is to evaluate the findings. This step may require going outside the data to see things like how teams are working together and to perform detailed reviews of the problem areas. It’s important to remember that data analytics doesn’t fix problems itself - it just shows you where to look. With a 360-degree view of employee productivity, this process will be much more efficient.

6. Deploy a Solution

With comprehensive data showing you where to look, the final step is to deploy an intelligent solution optimized to deliver the most significant impact on your bottom line. There may be situations where the answer is simply - you’re employees aren’t working enough. Much more likely, however, is that they don’t know how to best use their time. Or they are getting bogged down in an inefficient workflow or underperforming technology. Ultimately, any solution applied must be identified and quantified in light of the impact on productivity, which can only be achieved through a comprehensive view of employee productivity and business productivity.

If you are still reading this, and that process sounded complex to you - it is! The good news is with Grind Analytics we have packaged up that process into one integrated solution that can help provide the business intelligence solution your company needs.


Grind Analytics has pre-built solutions ready to be customized and implemented into your organization to provide business intelligence for your remote workforce.

Contact us today to see how quickly and effectively we can start improving your employees' performance - even while they're at home.

Grind Analytics offers a comprehensive business intelligence solution designed to be quickly integrated and adopted by your organization. It connects automatically to over 120 different industry data sources to present a 360-degree view of your operations and comes loaded with prebuilt dashboards and reports for an accurate measure of employee productivity.


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