Enhancing Employee Productivity with Data-Driven Decision Making
In fostering a data-driven culture, organizations aim to cultivate an environment where managers and senior leaders rely heavily on objective employee data for decision-making. To achieve this, leadership must identify critical data points, establish relevant Key Performance Indicators (KPIs), and implement tools for efficient data collection and accessibility.
Why Companies Must Embrace Hard Employee Data
When navigating projects and initiatives, it’s crucial to align them with company Key Performance Indicators (KPIs). Without relying on data-driven decision-making, well-intentioned endeavors may fall short of advancing these critical metrics. If your goal is to identify employee patterns of behavior like tool usage, slow vs. busy days, or productivity by weekday, agreeing on consistent KPIs is essential to make informed, unbiased decisions.
Numbers never lie, and basing decisions on data offers the advantage of objectivity. When data informs choices, it becomes challenging to assign blame to individuals or teams. Whether it’s optimizing task allocation, evaluating employee performance, or refining processes, data-driven decisions foster transparency. Moreover, this objectivity resonates with employees, as it minimizes the risk of subjective biases or preferential treatment.
Judgment and Critical Thinking Still Have a Role
While data provides valuable insights, it doesn’t always reveal the complete narrative. In data-driven organizations where bonuses hinge on numerical performance, accuracy becomes paramount. However, we mustn’t overlook the human factor. Employee data should guide management’s decisions rather than dictate them entirely. Staff and senior leadership occupy their roles due to their expertise—they possess invaluable knowledge that must be leveraged alongside data.
Curate The Right Tech For a Solid Foundation
Chances are good that simply using the data from your existing tools is not going to cut it. Some solutions that you can look at include:
- Marketing reporting dashboards (such as DashThis, Funnel.io)
- Business intelligence (BI) solutions (such as Oracle, Microsoft Azure, and various IBM solutions)
- Employee productivity monitoring solutions (such as Prodoscore)
The ideal solutions will have an easy-to-understand employee dashboard that pulls in data from various sources. Even if people in your organization are tech-savvy, it may be worth having a consultant set up the more complex solutions such as BI. If it isn’t done correctly, you may be missing data from key sources, which will create challenges downstream.
Avoid Confirmation Bias and Old Data
Once you have set up the right tools and established KPIs, it will be easier to eliminate confirmation bias and limit reliance on historical employee data. Confirmation bias is when an individual self-selects data that backs up their case; this is avoidable when everyone looks at the same data.
While there are some situations in which you have to base decisions on historical data, such as budget forecasting, having real-time data available allows you to pivot and do something like design a sales strategy based on current market conditions rather than historical ones from the previous year.
Confirmation bias and a reliance on outdated information can easily derail the data-driven decision making process so it’s important to pinpoint ways to avoid those challenges early on.
Educate Managers with Data
Once your new systems are in place, there should be extensive training for your managers on how to use them. While training is taking place, senior leadership needs to decide which KPIs will be measured against and which datasets and methods will be used. A clear policy then needs to be created for each department with reporting outlines and the general structure of a data-driven decision, which is:
- Defining objectives
- Collecting data
- Organizing and reviewing data
- Data analysis
- Forming conclusions
- Implementing and measuring
While it may be tempting to make some data only accessible to senior leadership, such as company financials or other sensitive information, doing this can severely impact the process by bottlenecking. To do their jobs effectively, your people need the raw data. This does not include confidential data such as payroll or employment agreements but should include items such as budget forecasts, gross revenue, and other more general financial and other information.
Data-driven decision making gives everyone in an organization a clear vision and guide from which to reach company goals. Defining what type of data you need and how to access and aggregate it is the hardest step but also the most important.
