An organization that prioritizes data in its strategy and operations often has an edge in its industry. With data, teams can make informed decisions, apply real-life statistics to new concepts, and use time and talent wisely. Learn how organizations deploy data throughout their workforce and how your team can too.
1. Improve Retention Rates
The cost to hire a new employee can quickly escalate, often representing a large portion of the would-be-hire’s salary. Teams that use HR analytics to identify candidates whose attributes align with the role can see improved retention rates. By filtering through the candidates whose predictive analytics don’t sync with the role, teams can find a good fit.
Candidates also benefit by having a better recruitment and hiring experience with predictive analytics. Pre-assessments used to identify work style preferences, collaboration style, and decision-making goes beyond what an interview can. Use these assessments to better understand a candidate, pairing it with qualitative data gathered in an interview.
Teams can use prescriptive analytics to inform decision-making, looking back on past experiences to make recommendations. HR teams can leverage past hire and onboarding experiences to improve them over time, enhancing the new employee experience. If past data shows that more training or networking was needed, future onboarding programs can incorporate them.
Data sets won’t always be housed within HR, so partnering with department leaders is critical for program effectiveness. Analyze prior performance reviews, feedback from exit interviews, and satisfaction surveys to identify strengths, opportunities, and weaknesses. This data can expose needed organizational changes like personnel, management style, and culture, all of which can improve retention.
2. Maximize Productivity
If you see a team member working diligently on their computer, it’s easy to assume they’re being productive. However, what may appear to be a dedicated worker may instead be a dedicated gamer. Reduce the need for supervisors to micro-manage by incorporating data analytics into their jobs.
Use task-tracking software to establish deadlines, responsibilities, and priorities across teams. Leaders can assign work with fewer touchpoints, saving time and creating a time-stamp for the task’s inception. Employees are notified immediately of their task and the software will help remind them of their impending deadline.
Employees can leverage this democratic access to data to manage their workload and managers can see who’s on-target. If one team member is falling behind, managers know immediately instead of when it’s too late. This way, they can determine if more help is needed, if deadlines need to shift, and when to hire more staff.
3. Produce More Effective Marketing Campaigns
Some may scoff at looking backward, but if you don’t know where you’ve been, you can’t know where you’re going. Collecting, analyzing, and scrutinizing past campaign performance and its reception is critical for creating effective campaigns. If organizations ignore prior performance, they may as well be guessing, which is a simple formula for failure.
Leverage marketing data to provide insights into prior campaign performance, what attention it earned, and what result it delivered. If your recent product launch of sturdy-yet-stylish travel gear went well, identify what strategies brought the most sales. Track key performance indicators, or KPIs, like email conversion rates and customer acquisition costs.
Analyze internal data like sales conversions against external data within marketing platforms, like social media. Your influencer campaign may have created a lot of buzz, but it was expensive to deploy. The data may indicate your influencer’s link doesn’t drive sales, but direct sales may show spikes aligning with their posts.
Without accurate campaign performance data, you might be tempted to cancel your influencer brand deal. However, when assessing performance across channels, you’ll realize that the value-add of social media buzz was a key sales driver. Identify the KPIs critical for your sales success and establish a methodology for tracking, analyzing, and assessing them.
4. Forecast Financial Demands and Risks
By analyzing past financial performance and market trends, businesses can create more accurate forecasts, helping them prepare for future demands. Predictive analytics can assess patterns in cash flow, expenses, and revenue, giving financial teams a clearer view of potential risks and opportunities.
For example, organizations can evaluate seasonal fluctuations in sales, identifying peak periods for revenue generation. This allows finance teams to allocate resources effectively, ensuring adequate inventory and staff during busy times. Similarly, tracking historical data on operational costs can help businesses pinpoint unnecessary expenses and streamline processes for better efficiency.
Risk management becomes more effective with data-driven insights as well. By monitoring industry trends, economic shifts, and competitor movements, financial teams can identify potential threats, such as market downturns or regulatory changes, and take proactive measures to mitigate those risks. With robust forecasting, companies can make informed decisions about investments, cost-cutting measures, and strategic growth initiatives, all while maintaining a healthy bottom line.
Collect, Analyze, and Empower Data at Work
A good data program begins with a plan and key to that plan is establishing a baseline dataset. Identify the type of data you have access to and how frequently you can collect and analyze it. Then, partner with your internal teams to set a cadence for reporting and analysis.
Be patient as you build your dataset, as several iterations of data or monthly cycles are necessary to identify trends. Apply, test, and re-test your findings in small batches before you apply massive changes to your business. With a data-centric approach, your retention rate can improve, boost customer engagement, and put your finances in the black.