Big data or machine learning offers some interesting applications when it comes to productivity. A recent study by the Society for Industrial and Organizational Productivity found that while most employees don’t flourish under large-scale, intense data mining programs in relation to decreased job satisfaction, attitudes about fairness, and privacy invasion, there are alternative situations in which data mining can actually promote productivity, motivation, job satisfaction, commitment, and performance.
One such instance in which big data can have a significantly positive impact on productivity is in the time tracking process. Getting employees to fill out timesheets is always a challenge, but incorporate some data mining and there are a few key ways in which it can improve.
Devise A Plan
Planning has always been important in collecting data, especially when it comes to time data. Never collect data for data’s sake, it just wastes time and annoys employees. Instead draft a concise plan as to your motivation for collecting the data, the specific data that’s needed, how it will be used, and how this is relevant to employees and their teams.
The plan should be rooted in an individual as well as a team and organizational success. This also helps to inform employees, as when they know why data is being collected they will be more accommodating in providing it.
Honesty and transparency are high on the list of best practices when implementing a time tracking process. Take note of and officially communicate how the data will be used (whether for corporate policies and procedures, or other related instances). Understand that timesheets are not performance reviews and as thus they shouldn’t be used as a disciplinary influence.
Employees should be aware of what kinds of data is being collected, at which times, what will be done with the information, and how this impacts on them.
Employees should also have some control in the process. Big data and machine learning can assist in this manner by speeding up or making it easier to fill out a timesheet, along with assisting in the accuracy of the data. The tools used for this should be in the hands of the employees themselves.
People filling out the timesheets should be able to decide whether and when to use the tools to make their tasks easier. This gives employees a sense of control and flexibility in regards to the type of information you gather.
Use Positive Feedback
Never underestimate the power of positive feedback. In regards to timesheets, the best feedback that someone can receive is that they don’t need to fix anything on the sheet. Eliminating superfluous corrections is crucial. Showing employees how improved data produced better decisions that lead to more benefits for them, their teams, and the organization as a whole speaks well to long-term success.
Your positive feedback should come from you, and not a machine and should focus on employee development rather than negative comments.
Finally, big data and machine learning aren’t a totally one-stop-shop solution. While some assumptions will mean greater success for one employee it won’t for another. A proper data mining process takes into account different cases and improvement over time based on the analysis of previous results. Understand how electronic monitoring practices might impact on some employees over other and be ready to make appropriate adjustments or more continual analysis so that everything is more productive and timely.
David Brown has been helping companies large and small since 1999 with everything from machine learning, to data center planning. He loves the space and writes about new and existing tech often.