How Can Analytics Optimize Employee Workflows?
Employee workflows are essential to the functionality of an organization. Yet, this is something that often gets forgotten, especially in businesses where it’s not such an obvious concern. Companies that boost efficiency on this front are going to be more productive, while also providing a better environment for their workers. Here’s how analytics can help optimize employee workflows.
Questions Can Get Answered
No matter the workplace, there are always issues that need a resolution. In the past, business owners didn’t always have the resources to effectively deal with these things. A pattern of trial and error was used until a reasonable solution presented itself.
It’s obvious why this isn’t a great system. First, it’s incredibly inefficient, as getting anywhere requires lots of wasted time and resources. And ultimately, you’re not arriving at an ideal endpoint—just one that works well enough.
Having data-driven answers to outstanding questions makes everyone’s life easier within an organization. It allows for maximal efficiency, while taking the guesswork out of the process. There’s also an important human element to this as well. Not having answers can weigh on the minds of employees. It can even create conflict when there are opposing factions that want to pursue different options. Analytics provides conclusive evidence for why certain actions will produce ideal outcomes.
Reappoint Tasks Based on Greater Efficiency
Workflow ergonomics is an extremely complex topic. The industrial revolution was a move by business owners trying to maximize operational efficiency—at the cost of their workers’ wellbeing. Humans aren’t machines and can’t be expected to perform tasks perfectly.
Data analytics, however, can help determine the best ways to appoint duties to create optimal employee workflows. Looking at hard evidence can show how tasks should be distributed, as well as which employees are best suited for them.
Reduced Need for Back-and-Forth
Many legacy BI systems are so slow and costly, they barely justify the cost-benefit from improvements. A huge part of this inefficiency comes from requiring dedicated teams of data analytics to process all queries. The thing is, not all questions are so complex that they should require an expert’s input. This ultimately comes down to old data systems being too complex for the layman user.
Modern analytics tools like ThoughtSpot are completely changing this. Major shifts in usability, thanks to features like search analytics, are making insights accessible to more employees.
Redesign Protocols for Less Internal Friction
Every part of an organization can be broken down into a protocol. From the layout of a warehouse to how people submit deliverables, every procedure can be improved. Data can help with this.
New technology makes data collection continuous and available for more applications.
Manufacturing and logistics are two areas that are seeing the myriad benefits of this revolution. For instance, data collection devices can be installed at every point in a manufacturing process. This will constantly collect massive pools of information, helping executives see exactly where to search for improvement.
Scheduling in the healthcare world isn’t nearly efficient enough. However, organizations adopting data analytics tools are finding ways to vastly improve these internal protocols.
Intuition Isn’t Always Right in the Workplace
One study conducted by the Economist Intelligence Unit for PricewaterhouseCoopers found executives in 2014 were much more likely to make choices on intuition and experience than data. Two times as many executives reported using the first approach.
Data is an opportunity for businesses to get ahead of the competition. Simply doing things because they seem like the right choice isn’t effective. Even if the result works out, it won’t necessarily be the best possible course of action. Employee workflows shouldn’t be managed by whims. They should be determined by facts.
There are many organizational elements that can be improved by implementing an analytics-first approach. Employee workflows are a prime example of this principle in action.
