An unprecedented confluence of intuitive tools, new predictive techniques and hybrid cloud deployment models are making Predictive Analytics more accessible to a wider spectrum of society and enabling capabilities for making intelligent decisions.

“We know where you are. We know where you’ve been. We can more or less know what you’re thinking about…” - Eric Schmidt, Former CEO, Google

The BIG Picture

For the uninitiated - Predictive Analytics is the use of data, Machine Learning techniques and statistical algorithms that predict future outcomes based on previous data. It can also be inferred as - technology that learns from experience to enable intelligent decision-making capabilities. As the name implies, Predictive Analytics use historical data to predict future events and guide decision-making. With more data, predictions may get better for a bunch of statistical reasons related to the normal distribution and robustness of individual statistics. A super simplistic representation to drive home the point around this topic: 

Predictive Analytics produce probabilistic estimates of the future. No one has a crystal ball that can predict with complete accuracy. Take horse racing for example. People place bets on horses using predictive factors like age, bloodlines, prior performance, etc. The odds reflect the combined predictions of all betters. Most of the time, the odds on favourite wins — performs as predicted. But, every once in a while, the long shot surprises everyone!

Predictive Analytics is not a new concept. Statisticians have been using decision trees and regression for years to help businesses correlate and classify their data and make predictions. What is new is that the scope of Predictive Analytics has broadened. However, it is no longer limited to mathematicians and statisticians. An unprecedented confluence of intuitive tools, new predictive techniques and hybrid cloud deployment models are making Predictive Analytics more accessible to a wider spectrum of society and enable capabilities for making intelligent decisions.

Predictive Analytics can empower businesses to augment historical data with real-time insights and then harness this to predict and shape future outcomes and is a key milestone in the analytics journey. Modern Predictive Analytics is about using machine-generated predictions with human insight to drive the business forward. In business, foresight is everything. If businesses are enabled to predict outcomes to a high degree of certainty based on experiences and data points, they will effectively be able to:

- Make smarter decisions

- Get to market faster

- Disrupt competitors

Knowing about higher probabilities of what happens next can improve Operations, Sales, Fraud Detection, Marketing, Crime Prevention, etc., and are widely applicable to any Industry, Business, Organisation, Municipality, State or Country!

The key to realising maximum benefits from the Human capital data lies in aligning tying the different data sources to strategic business objectives. Leveraging data from different sources along with the application of predictive models helps in projecting the right picture clarifying holistic analysis of the organisation.

Applying the Principles to Human Capital

With HR on the cusp of massive change especially in the post-COVID era – the adoption of analytics that impacts people continues to gain strong momentum, and it will not be long before human capital analytics becomes a required fundamental competency. Modern executives realise that people are their only sustainable competitive advantage. The demand for people-related analytics will continue to grow. By themselves, machines, materials, processes, technology, and information do nothing. People create value when they interact with those things and with other people. If people are 70% of your cost and all of your value, why would it not be a fundamental business practice to apply the power of analytics to maximise their net contribution?

Human resources are vital constituents for every organisation. In today’s age of competition and growth, it has become crucial to view people as assets rather than “costs” to the organisation. In a fast-paced world, skill requirements are constantly changing with rapid advancement of technology and regulations. Human capital dynamics demand that we apply analytics to reconfigure our workforce scenarios and predict our next best move or else we lose competitive advantage and market share.

In Predictive Analytics for Human Resources, Jac Fitz-Enz and John Mattox describe three levels of human capital analytics:

- Descriptive Analytics examines historical data to evaluate connections, relationships, correlations, and causations.

- Predictive Analytics uses past patterns to predict future patterns.

- Prescriptive Analytics takes prediction to the next level by using complex data to predict alternative outcomes to optimise the workforce.

Key Segments for Value Enhancement

Key segments where Predictive Analytics Can enhance Value for the HR domain include:

- Employee Segmentation and Profiling: Predictive Analytics can be leveraged for effective talent management by accurately segmenting employees which can help in understanding the employee base in a better way. A statistical relationship between profile variables (such as education and experience) and employee value enables HR to identify the most deserving profiles. This helps to increase quality and reduce recruitment cost extensively creating sustainable value for the organisation.

- Training and Appraisal: Predictive Learning algorithms can help predict the impact of organisational requirements and tailor the programmes accordingly for improved outcomes. Predictive Analytics helps identify employees with specific training needs as well as detect emerging trends in areas such as programme diversity, enrolment, onboarding, employee management etc.

- Forecasting of Human Resources and Recruitment Needs: Predictive Analytics helps to better forecast the organisational requirements by building targeted recruitment plans, optimising HR partner initiatives etc. This enables organisations to maximise resource utilisation and amplify appropriate growth and profit margins.

- Key Employee Analysis: HR professionals should capitalise on unstructured and structured data from multiple sources to create or redesign their initiatives targeted for Key employees at different levels. Key employee analysis is more effective than general employee surveys in getting fruitful and productive feedback. Such information can promote understanding of how various HR policies, initiatives, organisational changes are being perceived by the employees.

- Employee Fraud Risk Management: Predictive Analytics helps improve fraud risk management by enabling an organisation to identify employees who are at increased risk of noncompliance with the organisation’s security policy. Organisations can formulate a fraud risk score by analysing employee activity reports using statistical modelling techniques. This can help protect the company’s reputation and possibly prevent financial impact.

- Intangibles: HR function reports costs of various activities such as training, recruitment, appraisals, perks, incentives etc. Moving in line with strategic objectives, HR teams can increase their organisational presence by focusing on intangible assets (such as leadership, culture, commitment, loyalty) of the organisation.

Knowledge based on Predictive models can guide towards changes in leadership capability, engagement, culture etc. which can be used for better planning and predictions.

The key to realising maximum benefits from the Human capital data lies in aligning the different data sources to strategic business objectives. Leveraging data from different sources along with the application of predictive models helps in projecting the right picture, clarifying holistic analysis of the organisation. Blending of statistical information from government and other sources along with organisational data provides a clear ground for effective planning and meeting both short term and longterm goals of the organisation.

To play a more strategic role in the organisation, HR teams need to move ahead from operational analytics to predictive competence and helps them play a bigger role in driving strategic organisational vision and objectives. Predictive analytics helps organizations in boosting superlative employee experiences that will help in achieving projected long-term goals with desired optimum efficiency