In today’s fast-paced society, time management is of huge importance to everyone in the developed world, from individuals, to small businesses and big organizations. With the latest developments in big data analytics, and its more widespread availability and usage, there is a growing number of businesses and enterprises which are choosing to implement big data analytics in some, or in all of their business processes.
One of the processes where big data can have a beneficial impact on a business, or an organization, is time management.
In this article, we will discuss:
- Why time management is important for business
- How big data can be helpful in managing time
- Things to consider before data mining implementation
- Steps for implementing big data for time management
Why is effective time management important for business?
Time is money. Sure, it sounds like a cliché, but it’s true. As a matter of fact, money and time are quintessentially scarce resources. Most people are always lacking the one, the other, or both. The same goes for a business. If you manage your time right, you can produce more products and provide more services, hence have more money. If you have a substantial startup capital, but do a poor job managing employees and time, eventually, you’ll go broke.
With a rightly tailored time management strategy, and powerful time management software, businesses can:
- Prioritize tasks
- Keep productivity high
- Have insight into everyone’s time results
- Track project deadlines
- See if all employees are at work
- And much more
How can Big Data be helpful in managing time?
When the right data is tracked, it provides crucial insights to business owners and managers, about overall and specific performance issues in their company, or department. One of the simplest things to do, in order to increase productivity, is to track time with the right cloud-based software.
Collected data can then provide valuable information about how much time each employee spends on:
- Designated tasks and projects – how long it takes an employee to achieve certain goals, and how he or she compares to other workers
- Meetings – how much time meetings consume from employee’s work hours, and whether there is a need for increasing or decreasing their frequency
- Covered mileage – business mileage is used to measure every business-related driving, excluding commute times to and from work. Businesses can get a 54.5 cent deduction for every business mile your employees travel. So, this also helps save money.
- Breaks – are employees taking frequent breaks? How much time do employees who smoke spend on breaks vs employees who don’t smoke, etc.
- Lunch – does everyone respect lunchtime?
- Any other workplace activity that is significant to employee’s productivity.
By analyzing this data, you can find trends that impact the company’s overall performance, and find a way in which you can maneuver, and streamline productivity, as well as time management.
But, for big data management to be successful, with your employees on board with the organizational data mining practices, some standards must be met.
Things to consider before data mining implementation
Research done by SIOP has shown that there are four issues that need to be considered when dealing with employee attitude towards performance and time tracking:
Giving employees a sense of control when collecting their data
This point focuses on the ability of an employee to delay or prevent data collection. Some studies have shown that employees who have more control over the data tracked have higher performance and motivation in their everyday work activities. On the other hand, employees who had less control over the data collection process have shown:
- lower job satisfaction
- lower task performance
- lower perceptions of organisational fairness
Data collected is of job’s significance
This should answer the question of whether the data collected is of importance to a person’s job. Researches have shown that if the information collected is relevant to the job; employees don’t perceive it as an invasion of privacy. This can lead to increased belief in company fairness regarding its procedures and policies.
Impact of the data mining intensity on employees
If the data is collected often, and the employee’s perception of the mining intensity is high, this can lead to emotional exhaustion and decreased well-being.
Other common side effects of frequent and aggressive data mining can be:
- depression
- reduced job satisfaction
Feedback about the collected data
If the data collected about the employee’s performance and time management is used to provide a constructive feedback, people will perceive the data mining process as something meant to help their development, and not as something punitive. This can lead to higher job satisfaction and organizational commitment, as well as an increased sense of fairness.
Steps for implementing big data for time management
- Make sure you know why you are implementing data mining in time management, and then take time to develop a plan relevant to individual and organizational success.
- Always be transparent about collecting information, and be sure you have disclosed your intent and purposiveness behind data mining to your employees.
- Give your employees a sense of control and flexibility, by allowing them some freedom in the data collection process.
- Try to always provide a constructive feedback related to the data collected, and show the benefits of tracking data for time management purposes.
- Acknowledge personal differences, and refrain from trying to fit all employees in the same mold. Good data collection should cover a variety of use cases and scenarios.
Conclusion
Implementing data tracking and timesheets into your organization’s management shouldn’t be a burden to your employees. If you listen to these key takeaways, use the right time tracking software, and use collected data for the development of both your business, and your employees, nothing will stand in the way of successfully streamlining your organization and mastering time management.
Do you use big data for time tracking and management in your company? What are your results and observations? Please let us know down in the comments.
