RedEye WFM & Microsoft Power BI: the tech stack that can keep offices COVID-19 compliant

2 December, 2020

Maintaining COVID-19 Compliance 

I’m almost certain there isn't a functioning business out there in the world today that hasn’t had to face the intense data collection requirement imposed by COVID-19 regulations, especially as employees return to part-time office-based work 

It may seem rudimentary, but even for sophisticated operations, maintaining COVID-19 compliance in this regard means eating into time and resources that are better spent on their clients and their business.  

A simple efficient solution  

This tech stack functionality using RedEye WFM and Microsoft Power BI enables organisations to optimise a variety of functions reducing manual resources impact. One example is managing office attendance - a compliance requirement in line with COVID-19 regulations. An organisation can track office entry for their staff through the WFM app. The WFM data can then be exported through an API to serve it to a Power BI dashboard for up to the minute information about team members who are in the office.  

All the staff would be required to do is check-in through the RedEye WFM app from their mobile device and attendance data is captured in a compliant manner – the rest of the process is automated from the end user’s perspective.

Above: Data is exported from the RedEye WFM app through GraphQL API in JSON file format and served to dashboards in Power BI for analytics. 

How the RedEye WFM + Microsoft Power BI combo can deliver value to businesses   

This clever tech solution is simple at heart can deliver big benefits back into businesses. Time and money associated to reducing resourcing implications means it can eradicate the requirement for personnel to execute these functions manually. This delivers the opportunity to shave tens of thousands of dollars of annual operating costs. 

And this stack has risk mitigation benefits as well because leadership can make important decisions about the health and wellbeing of their teams and their office environments, backed by accurate data and delivered with speed.  

Being able to rely on usable and valuable data is pivotal - users can see when the office is busiest, or who's in the office that day or on any given day and make decisions about capacity, managing workforce resources relative to core project delivery and business operations. 

How do you deploy this?   

Using GraphQL to fetch the exact data refines searchability - when you visit search you can pick and choose which columns to include in your search results. This is GraphQL in action - selecting which data fields you want to include. Connecting this API to Power BI means it is running searches and giving back the data fields you requested, facilitating results served for analysis.  

In this instance, using GraphQL also solves overfetch and underfetch problems. This avoids overfetching, where there is data in the response which you don't use, or under-fetching where you don’t have enough data and forcing you to call a second endpoint. 

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Above: Sequence of calls through PowerBI in the R scripting language to deliver data for analysis.

This allows a user to export their WFM data containing jobs, assets, issues, locations and groups in JSON format. 

Most work management platforms which gather large and rich data sets struggle to give meaningful access to their  user's data, which basically means it’s not being used effectively.  

The first benefit of this feature is that it breaks down the barrier between the rich data set and the 3rd party tool (in this case Power BI) without complex and expensive integration work - no additional connectors are required.  

The second benefit is that the data is extracted using JSON file format, which supports time series data. This means we aren’t extracting a flat table of information as would be expected using a CSV, rather we have the additional dimension of time which delivers a rich base for analysis. Anything that you see in search can be brought into Power BI for analysis. Once Power BI has the data it can be visualised and analysed on the fly.  

By connecting directly to the WFM API instead of using a manual export, the data can be analysed on demand in a near real-time fashion. This entire process can be completed only in 1-5 minutes, depending on the size of the data set. 

Early conversations with clients about this integration have highlighted the sort of process efficiency that is possible – from the simplest things like this health and safety workforce management example to streamlining more major business challenges like compliance and maintenance management. This reinforces the value of making your data more usable, available, relevant and secure 

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