5 Ways to Use Data to Increase Productivity
By AVON COLLIS
Data is a fact of life. It’s everywhere. Everyone is making it, everyone is acquiring it and everyone is using it. Or are they?
It is true that 90% percent of the world’s data today has been created between 2016 and 2018, and since then we have been doubling the data production rate every two years. But the vast amount of digital information is still falling through the cracks. And it’s taking valuable insights with it. In fact, research shows that only 4% of companies make good use of data analytics.
According to Experian Quality Data, ‘Fully 53% of chief data officers believe lack of data access is the biggest barrier to success for their company.’ Missed data is missed opportunity – especially for businesses that are looking to grow their impact (and their bottom line).
Why Don’t All Businesses Use Data Effectively?
If you’re concerned that you aren’t acquiring enough data or using the data you have effectively, you’re not alone. Most companies aren’t acquiring the data they need to be successful. And many companies also don’t do a good job with the information they already have. They don’t know how to manage it, analyse it in ways that enhance their understanding or make changes in response to new insights.
Developing the ability to acquire and assess your data is essential to increasing your productivity and driving the further success of your business.
5 Ways to Use Data to Increase Productivity
1. The problem – ‘Selfware’
‘Selfware’ is unused or underused software. It might be an outdated (and clunky) system that employees continue to use due to familiarity. Or it might be an application that really brings no value to your business but has a high ‘per user’ cost.
This isn’t a one-off problem. In fact, 93% of surveyed businesses report wasting money on selfware.
The Solution – Time tracking app
The key to understanding selfware is tracking application time use. Time tracking apps help you see the amount of time spent in an application, where applications are being used and actions are being logged.
Once you have this information, you can then retire outdated or unused applications that are sucking your team’s productivity.
Example: DeskTime
2. The problem – Idle time
Studies show that over 78% of employees experience idle time at work. Not only does the lack of productive time drain resources, idle time also makes workers bored and stretches out work that could be done in a shorter time.
The Solution – Time clock app with basic tracking features
Understanding when your team is the most productive allows you to make strategic decisions on employee working hours. If you understand that your team’s peak productivity is first thing in the morning or late at night, you can better structure working schedules, important workflow meetings and deadlines to reflect your productive hours.
Example: Hours
3. The problem – Lack of evidentiary problem solving
A lack of hard data can lead us to making off the cuff or blind decisions. This can be especially difficult to manage in situations where time is short or emotions are running high (such as in times of disruption, like COVID-19).
The solution – Data driven decision making
Data encourages well-informed decision making backed by hard evidence. And the more data that businesses analyse, the more helpful it becomes. Data analytic engines actually become smarter as they absorb a company’s actual outcomes and connect them to the data being collected. And without the emotional biases of individual decision makers.
Example: Apache Hadoop
4. The problem – Challenges in staffing
Finding qualified new hires can be challenging, especially in high-skill roles and industries. And this can cost you real dollars. One survey showed the cost of a bad hire can reach up to 30% of the employee’s first-year earnings. In another study, 74% of companies admitted they’ve hired the wrong person and have lost an average of $14,900 each time.
The solution – Predictive algorithms
Data-driven companies that use algorithms to predict the engagement of potential employees when helping managers make hiring decisions have increased productivity and better customer outcomes, which leads to real dollar savings. One company who utilised internal data analysis found a 5-10% improvement in customer resolution rates, which translated to a total savings of $5 million to $12 million from a single data-driven initiative.
Example: SWOT analysis
5. The problem – Sick employees
Health is a chief factor in productivity losses. When employees are sick, costs increase. In the US, poor worker health costs employers $530 billion a year. This comes from lost productivity due to worker absence, chronic conditions that cause ‘impaired performance’ and workers compensation.
The solution – Data driven health initiatives
Understanding the impact of health on productivity through data allows you to create and implement solutions to combat poor employee heath. These might include in-office meditation rooms, and ergonomic designs, such as standing desks. When health increases, so does productivity.
Example: Springbuk
Takeaway – Making Good Use of Data Analytics
Making good use of data means leveraging the right combination of people, tools and data with the outcome that you drive improvements in your business. Data initiatives help you save money and scale your business by accurately predicting the future behaviour of your target market, rather than guessing at it.
When you’re a forward thinker, which means you’re better able to manage your teams, your systems and your processes to become more productive and profitable.
