Mrs. Dorcas Wainaina Executive Director

Kampala August 2018

TRUE HR TRANSFORMATION

and Evidence Based Policy Making: The role of Human Resource Data Analytics

DISRUPTION

• Tesla Inc. –electronic cars – charges batteries remotely

• Make solar roofs –roofing industry and power companies

TRANSFORMATION

TRANSFORMATION

TRANSFORMATION

• The scope of the public service in Africa has changed in terms of size and complexity of services provided.

• Public services are now provided to populations which are much larger, more demanding and increasingly more informed about their rights and obligations.

• Human resources management in the public service today has the more challenging task of ensuring that employee performance meets the complex expectations of the growing and informed populations, as well as political leaders.

PUBLIC SERVICE CHANGES

• The framework for human resource management in most African Public Services is enshrined in the respective countries’constitutions and in Services Commissions Actsthat provide the institutional arrangements and regulations for the administering and managing of the public service.

HR FRAMEWORK

DATA Today

• Volume

• Capacity

• Veracity

• Uncertainty

• Velocity

• Quantitative

• Qualitative

• Triangulate

• Energy

• For years, companies have analyzed data of all types –customer, product, financial – with one important exception:human resources data.

• HR departments have largely shunned analytics and focusedon automating previously manual personnel processes.

• The result? "At the end of the day, executives have had a leveron marketing spend and product development spend,"Thomas said (Forrester Research), "but they've never reallyhad a lever on people."

• That needs to change, -- and fast. HR must manage workerslike strategic assets, and one way to do that is with HR-baseddata analytics

HR Analytics : Background

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• Metrics, analytics, predictive analytics and big data are all phrases that are used often regarding measurement in HR.

• This issue for HR professionals today is, what do they all mean and how do we make sense of it all?

Metrics, Analytics, Predictive Analytics

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• Analytics is a key function undergoing rapid growth in businesses across the globe

• Compared to companies, the majority of government agencies have yet to even start exploring the potential of HR analytics.

• In general, the public sector is still lagging in the adoption of Data Analytics.

HR ANALYTICS

• Also known as People Analytics.

• use of people-data in analytical processes to solve business problems.

• uses both people-data, collected by HR systems (such as payroll, absence management) and business information (for example, operations performance data).

• HR analytics enables HR practitioners and employers to gain insights into their workforce, HR policies and practices, with a focus on the human capital element of the workforce, and can ultimately inform more evidence-based decision making.

HR DATA ANALYTICS

HR analytics does not only gather data on employee; it provides insights into each process by using data to make relevant decisions, improve processes and operational performance

HR ANALYTICS

PAST

• HR primary goal- collect and keep track of employees personal and professional information i.e. payroll, health benefits, performance reviews, salary rates, annual numbers of retirement

NOW

• HR Analytics - to interpret data, analyze trends or issues and take proactive steps with departments to keep the organization running smoothly and profitably.

HR – Years Past and Now

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• Ability to spot trends

• Retention Problem

• Use software in making predictive analytics to help you make wiser choices based on historical data.

• Collect data about workforce over time and look at it holistically

• HR need an interpretive skill – its the ability to speak like the rest of the business

Here comes HR Analytics...Ready or Not

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• Is not the same as Metrics

• Goes beyond gut feeling

• Allows you assess information dynamically

• For example: Study your workforce now, failure to do now means ill-prepared for what is to come.

• Prediction: It is one thing to know what has happened in HR but another thing to know what will happen.

– For example, HR groups report the % of people that completed an engagement survey. This type of reporting relates to the process orientation of HR and, although interesting, does little to demonstrate the true value of the functions.

HR Analytics…

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• HR metrics: quantify the cost and the impact of employee programs and HR processes and measuring the success (or failure) of HR initiatives.

• They inform Analytics

• It is not metrics insights alone, but the ability to quickly build comparisons, identify trends and find outliers that makes the difference.

What about HR Metrics

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Basic and standard metrics used by many organizations in measuring HR performance

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Calculation Formula

• # days absent in month ÷ (average # of employees during a month x # of workdays)

Calculation Frequency

Monthly

Clarification rules

• Days absent = sum of all man days of absence for entire employee group

• Average # of employees = (opening # + closing #) ÷ 2

• total cost of employee benefit/program ÷ total # of employees

• Depending on frequency at which program costs are incurred:

– Monthly

– Quarterly

– Annually

Examples of benefit/program costs:

• Group membership to clubs

• Group medical cover costs

• Company transportation costs

• Etc.

• annual benefits cost ÷ annual salary

Annually N/A

Absence rate

Benefit or program costs per employee

Benefits as percentage of salary

Metric/KPI

• annual salary ÷ total compensation (salary + benefits + additional compensation)

Annually Additional compensation includes bonuses etc.

Salary as percentage of total compensation

• compensation (or benefit cost) ÷ revenue

Annually Other employee cost elements can be measured against revenue to assess productivity

Compensation (or benefit) to revenue ratio

• Improved and Faster decision-making• Improved profitability• Improved ROI and contribution for the HR function• More accurate planning and forecasting• Better Workforce performance• Identification of key risks before they affect the business• A source of competitive advantage for organizations• More and Better Relationships Across the Organization:

Making it Easier to Communicate and Engage with Others, Collaborate on Solutions, and Influence Business Outcomes – Having access to consolidated and actionable insight, leaders

are using the data and visuals as a basis to meaningful conversations with the business.

• Empowering Managers: Leading to Ownership, Accountability and Taking Action for Business Problems– information that is segmented and relevant to their group helps

managers make right decisions

Benefits of HR Analytics

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Succession Planning

• Age

• End of service

• Transition

• Prepare for new talent

• Source of new talent

• To hire the best is not enough to introduce them to their new duties and guide them through professional training programs.

• They need to adapt to corporate procedures and then to learn all details about their positions

• When this phase is over, it is necessary to keep learning because the vast majority of businesses are constantly upgrading their services

• While you’re spending time trying to train and retrain the new hire, your business will suffer

• Employees attend online courses, training sessions, and other learning programs. However, it is hard to determine the exact benefits of such procedures.

• data science has the ability to examine employee learning and to conduct the cost/benefit analysis for every single course they organize.

TRAINING & EVALUATION

Time Management for Productivity

• Biometric

• Sign in

• 8.00 am - 5.00pm

• Overtime

• Jacket on seat

• Seasons

• The analysis of employee performance is one of the most important features of Analytical HR.

• This system enables an organization to monitor all key performance indicators in real time and to evaluate each one of its workers separately.

• Big data analysis also detects potential mistakes and flaws in work, a valuable feedback that can be used to make things right in short notice.

EMPLOYEE PERFORMANCE

Challenges to Analytics

• Our Current Dataset

• Government leaders will also often react to the idea of analytics with, "We don't capture enough data yet."

• But the goal of analytics isn't to have the most data — it's to find the right data, which is often readily available and sitting idle in your system archives. For example, if an agency's biggest challenge is retaining good talent, an answer is likely buried in the unused exit interview and turnover data from years past.

• Returns of analytics

• HR departments that lacks know-how

CHALLENGES TO ANALYTICS

• Lack of know-how

• The major barrier hindering implementation HR Analytics is not a lack of

data on employees – salary information, performance reviews, education

level – but silo-ed employee data

• Many HR systems and applications are not integrated with financial

systems.

• A lack of historical data against which to compare HR analytic results

makes measuring ROI tricky but a change of even a percentage point or

two in employee retention or turnover can have a significant financial

effect.

• HR analytics is for companies of all sizes "The cost of hiring someone

doesn't change based on the size of your organization "and the cost of

people not performing doesn't change either."

Making HR Analytics a Reality

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• Self education – Read as much as you can and network with peers

• Understand the difference between Metrics and Analytics – Time to Fill isn’t an analytic. It is a number. Analytic is predictive.

• Understand the business goals for a clearer idea of how HR Analytics can serve your company

• Confer with Business Leaders and start small

– Ask your business leader what metrics they are holding you accountable for to understand what information could help them be successful.

• Keep your HR analytics small and simple initially and go for a few quick wins

• Sometimes disagreements among Executives and business units over accuracy of HR data e.g. headcount number and inconsistent definitions. Be accurate

• Build a diverse HR Analytic team – HR, Statistician, Consultant

– Numbers only will lose the point. Tie numbers to people, behavior, motivation, culture.

Make HR Analytics a REALITY…

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