Management consultants and investors are under increased pressure to deliver exceptional results and exceed client expectations. In a highly competitive marketplace that changes daily, new challenges arise that demand innovative solutions. The key to success is strategic investment in data that drives better business decisions.

Such investment translates into valuable insights that identify trends, optimize resource allocation, and anticipate market shifts. This approach ensures a company not only meets but consistently exceeds its goals and objectives, paving the way for sustained success and a clear competitive edge.

The Power of Data

Research by Gartner shows that 83% of business strategies fail due to faulty assumptions. The best way to ensure these strategies succeed is to use data to benchmark organizational performance.

In the realm of human resources, data can help measure employee successes and failures, determine the effectiveness of human resources teams, and benchmark against industry competitors.

Investors can use data to evaluate portfolio health and strategic direction, unlocking business value and transforming organizations into more intelligent and trusted enterprises.

Data can also be used to promote better decision-making that aligns with regulatory requirements, reduces risk, and helps with forecasting and meeting financial targets.

Workforce Management

SaaS workforce analytics platforms like Aura play a pivotal role in providing the right data to drive private equity, hedge funds, and management consulting recommendations. Aura's HR data, sourced from public job postings and other external information, helps pinpoint operational targets:

• Planning: Uncover trends and make forecasts, which are essential for informed planning and organizational growth. Aid in developing business objectives, right-sizing, and securing the right talent.
• Strategic talent management: Identify talent needs and gaps, areas for development, and retention strategies.
• Cost optimization: Analyze recruitment, training, and turnover costs. Spot cost-saving opportunities, justify expenditures, or calculate ROI.

Useful Examples

Data can answer questions and propose solutions with concrete evidence. Take, for example, four different analytic scenarios:

Descriptive analytics (what happened): Analyzes historical data to understand what has happened in the workforce over a specific period.

• Example: Wal-Mart Stores, Inc. focuses on job tenure, turnover, and career movement to monitor the effects on customer experience and sales. This helps them establish roles and paths for employees, especially in relation to talent development and business continuity.

Diagnostic analytics (why did it happen): Examines data to understand the causes of past events and behaviors within the HR domain.

• Example: Juniper Networks uses big data to analyze where top-performing employees come from and where they go when they leave. This allows them to seek out and integrate the freshest management values and connect them with performance objectives.

Predictive analytics (what might happen in the future): Uses statistical models and forecasts to predict future HR events and employee behaviors based on current and historical data.

• Example: Royal Dutch Shell compared results from employees playing video games designed by neuroscientists against real-world HR data to identify people who tend to have the best ideas. They used the information to identify six characteristics of individuals whose ideas were likely to succeed. The result is an increased ability to focus on actionable suggestions and improve their business on a continual basis.

Prescriptive analytics (what to do next): Provides recommendations on how to handle future situations and challenges in HR by analyzing potential outcomes and scenarios.

• Example: Microsoft develops statistical profiles of employees who might be a flight risk from data and creates HR intervention strategies such as mentorships and growth planning to slow attrition.

Creative Freedom

Companies do not openly reveal how they use data related to payroll, benefits, hiring, onboarding, employee performance, or overall morale because it is often used as a magic bullet to stay ahead of the competition and enhance profitability.

However, there is no doubt that such insight, when used creatively and logically, builds opportunities for management consultants and investors to support business growth and productivity.

Conclusion

The importance of data-driven investment strategies is undeniable. By adopting the use of such tools, fueled by workforce management analytics, experts can help businesses make more informed decisions that ultimately enhance revenue and performance.

This ability to interpret and act on data sets leaders apart. Now is the time to embrace using data as a game plan for securing a position as an industry pacesetter. By doing so, consultants and investors can consistently exceed client expectations and achieve sustained success.