You’re an HR executive of a multinational corporation with thousands of workers in diverse business lines.  Do you know how many account managers the company employs and whether they all do the same kind of work?

How confident are you that you’ve identified all employees who need to be trained in order to comply with regulatory requirements? Is your compensation benchmarking accurate enough to answer legal questions about equal pay? 

The most effective business decisions are based on having accurate people data, but chances are you don’t have it. Instead, your company’s data is likely siloed across locations, departments, and divisions, having been sliced and diced by mergers and acquisitions, parsed by local users, and buffeted by periodic expansions and contractions. 

Each day your company’s senior executives take actions based on their understanding of how employees are paid, deployed, and allocated across functions, jobs, and locations. But if your people data is unreliable, what is the true value of those decisions?

Flawed people data is a familiar issue, and fixing it is often stymied by confusion over where to start and which group “owns” the problem. But accurate people data starts in HR, during the employee onboarding process. So why shouldn’t HR also be at the forefront of transforming the current jumble of inconsistent information into an accurate, accessible resource for decision makers? The key for HR to succeed in this transformation is creating and implementing a data simplification plan.

In Search of Consistency and a Common Language

The goal of any organization is to have the right people in the right place at the right time, and be able to account for the cost. But that goal is elusive without people data standards that have been agreed to by HR, IT, and the enterprise. 

Consider the case of a California-based consumer loan division of a large financial services institution that planned to consolidate several business units. The initial financial report to the CFO showed the units spent $85 million in salaries during the previous year. Yet, a subsequent audit revealed the salary total to be substantially more—$180 million. The problem? The two units had different definitions of what constituted “salaries,” with one definition excluding bonuses and payments to temporary workers and contractors. 

Hidden pockets of people data, as in the example, thwart successful decision-making. But the impact goes deeper. For instance, incomplete or inaccurate people data hinders the ability to make informed decisions about workforce planning, and it can complicate or prevent the use of efficiency technologies like SaaS and Cloud for payroll processing. 

The Basics of Data Simplicity

Most companies maintain data in similar ways.  A majority of information is held in corporate systems, a lesser amount resides at the divisional level, and residual key facts are stored at the line manager level. This creates tension between the top and bottom of the organization. Moreover, many important decisions are made at the center where the data may be the least accurate. 

To address people data problems, you need to simplify and streamline your body of information to create a ‘system of record’ that is integrated throughout the organization and kept up to date.  Whether your company is a complex global corporation or a small regional enterprise, there are four basic requirements for accomplishing the task: 

1. Develop Consistent Standards. Having global definitions for key data elements is a baseline requirement for information transparency. Job titles, for example, must mean the same thing across divisions and geographies. This will facilitate the use of employee self-service and manager self-service processes since the entry values will be the same across the board. 
2. Address the Need for Flexibility. Global data helps drive the organization’s strategy and is essential for top-line needs like group reporting.  Such data must be standardized and managed centrally. But divisions and groups on the ground need to be able to adapt some types of data for local reporting needs. You need to define the boundaries between global and local data in your organization and patrol the border.
   To address people data problems, you need to simplify and streamline your body of information to create a ‘system of record’ that is integrated throughout the organization and kept up to date.
3. Eliminate Data Duplication: Data duplication results when users inadvertently create data fields that have ambiguous or overlapping meanings. Sometimes such duplication is deliberate in order to create special reports. Each data field in your people data should have a clear and consistent meaning and represent a single state or event. Structured codes, sometimes called ‘intelligent’ codes, should be avoided.
   
4. Provide all users with some automated integration. Core systems must be linked to provide reliable people data to all users.  Your HR systems, for instance, must be automatically integrated with other key systems such as payroll. Key automated worker feeds should start with security, email, and directory applications.

Taking Steps Toward Data Simplification

Addressing your people data challenge does not require fixing everything right away.  As the HR leader, you know where your company’s pain points are, so your first step is to identify a specific pain point to address with a data simplification pilot program.  Then take the following steps:

•  Form a team. IT needs to be your partner in this assessment and in any systems changes to address identified technical issues. The business also needs to be represented, and how you choose your business partner depends on how the organization is structured and how you’re launching the project. For instance, it could be the head of an individual division that’s part of the pilot, or it could be the office of the CFO.

By simplifying your data and taking charge of the processes around it, you can liberate your organization to do a wealth of things successfully. 

• Identify the key people data elements for the pilot. These data points need to be accurate, consistent, and easy to locate in order to alleviate the specified pain point—and they need to have (or be given) consistent global definitions. Examples include job descriptions, management level, base pay, and total compensation.
• Assess the current people data surrounding the pain point. Look for patterns of errors, overlaps, and “dirty data” that can be adjusted to get a handle on the size of the pilot program task. For example, how many duplicate job descriptions do you have? Is the definition of base pay consistent company-wide? 
• Identify and evaluate your application landscape. This includes your technologies, practices, and processes, including everything from corporate and division data systems to end-user developed applications like spreadsheets.  Applications already working well can be the basis for standardization into a single, simplified global data system.
• Establish criteria for evaluating the new system as it’s deployed. Set up governance for the new system to transition it beyond the pilot into other parts of the organization with an eye toward how you want it to work on a global level and how to make it sustainable.
• Create a realistic deployment plan for your pilot. Focus on incremental progress and well-defined business outcomes. The tighter you develop the plan and demonstrate the benefits, the easier it will be to ameliorate potential resistance. Success will create momentum to build on throughout the organization.

Simple Data, Smart Decisions

Businesses exist in a state of constant change, and poorly managed people data can compromise the ability to make well-informed decisions at all levels of the company. By simplifying your data and taking charge of the processes around it, you can liberate your organization to do a wealth of things successfully. 

Consistently accurate people data improves cost management, eliminating hidden expenditures and facilitating trustworthy company-wide insights that can drive the business. Eliminating duplicate data lets you provide all users with automated integration to reduce maintenance costs. And with consistent standards, you can capitalize on the benefits of shared services.

Accurate people data starts in HR during employee onboarding, and that makes HR the natural leader for data simplification. Enlist IT and the business side in a collaborative effort to prove the value of data simplicity with a controllable, measurable pilot project that eases a specific pain point. By incrementally moving forward as a team, you can build on your successes and create a portfolio of demonstrable benefits for your organization. 

Get in touch: global.consulting@wipro.com.