Improving HR leadership through effective decision support

IMPROVING HR LEADERSHIP THROUGH EFFECTIVE DECISION SUPPORT

T o n y M o r g a d o

t is ironic that, traditionally, human resources departments have been responsible for collecting all legally and organiza- I tionally required information on employees, yet this informa-

tion was either lost in tons of paper files or trapped in databases, and locked away from the human resources staff. The explosion of user-friendly databases, client-server HR systems, and reporting tools has moved us toward a functional users’ information age in which the HR professional, for example, can access, manipulate, and extract HR information and commingle it with other organiza- tional data. At a minimum, these systems can help streamline business processes and ultimately provide liberal access to data for strategic analysis. This article examines how thegoodguys!, Inc., has used its new information management system and decision-support tool to supply data for business analysis and to improve the efficiency of business processes.

Tony Morgado is HRIS Manager forthe good guys!, Inc., a leading consumer electronics retailer. His human resources background includes labor relations, training & development, and HRIS administration. Most recently he managed the development of a multimedia sales training program and the development of the good guys! new human resources management system.

DEFINING USER NEEDS AND SATISFACTION The good guys!, Inc., is a consumer electronics specialty retailer

founded in 1973. The company has 76 stores currently operating in Washington, Oregon, California, and Nevada, and has approxi- mately 4,500 active associates who are committed to offering customers a superior consumer electronic shopping experience. Like many retailers, the company has a high-volume HR administration function. This function is supported by extensive recruiting efforts as well as robust sales and product and management training programs.

Prior to the implementation of a new human resources management system (HRMS), HR functions were supported by a home-grown system that captured information that at one time was adequate. Though the old system allowed for the input of information, there was no easy tool to extract the data for analysis. The only means to retrieve data and support the human resources function was through intensive front-line manual intervention and a deluge of paperwork.

Company management recognized that the old information system could no longer support the current needs of the business. It was decided that, because of the nature of the business and the

Employment Relations Today Spring 1997 51 CCC 0745-7790/97/240151-08 0 1997 John Wilev 8 Sons. Inc.

Tony Morgado

D a y-toda y human resources administration efforts can be daunting.

business cycle, the company would fast-track the search for a new information management system. After a two-month software evaluation/justification process, a packaged system called “HR Stream” was selected.

During the implementation of the new HRMS (which took about six months), we met with our staff and users throughout the organization to ensure that we had a well-defined mission and expectations of the new system. The purpose was to define and target the goals at the initial stages of implementation as well as to guarantee that future system development would also meet these goals, which are the following:

Improve processing efficiency. Create business analysis tools. Increase data accuracy. Eliminate redundant data manipulation. Enhance management reporting.

By achieving and continuing to drive toward these goals, we will keep the HR department in the forefront of the organization, making it a driving force in measuring the company’s ability to meet its goals.

IMPROVING PROCESSING EFFICIENCY Day-to-day human resources administration efforts can be a

daunting task. In the case of thegoodguys!, Inc., the company hired and trained about 2,000 regular associates in 1996 and, during the busy Christmas season, processed an additional 1,100 temporary associates, resulting in a high-volume human resources department. Obviously, regulatory as well as company-required information must be maintained on all these associates.

In the old days (prior to September 1995), our human resources staff had to maintain ”tickler” paper files on each of these associates to ensure that each associate had supplied all of the required information during the orientation process. During our preimple- mentation analysis, it was determined that an HR representative could spend up to two hours a day reviewing these tickler files and identifying those associates with missing paperwork. It was clear that this manual method of record retrieval was counterproductive.

During implementation of the new HRMS, the methodical design process used by our consultants, CDG & Associates, Inc., of Dallas, Texas, guaranteed that all of the necessary data to automate the orientation (for new hires) verification process was being captured. As a result, we were able to develop reports that highlighted those associates for whom there was missing informa-

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B y using the decision-support system, we are no longer restricted to developing staffing information on a weekly basis.

Improving HR Leadership Through Effective Decision Support

tion. In addition, some of the orientation documentation has expiration dates (as with drivers’ licenses for truck drivers, for example) and, by capturing those dates in our system, we were able to produce reports that show associates with upcoming HR data deficiencies. Thus, the new decision-support tool used to retrieve the information (we selected Geac’s Decision Support Tool delivered with HR Stream) eliminated a mundane, unpro- ductive data-gathering process so that HR representatives can perform vital storesupport functions. One standard we apply to all audit or data-gathering reports is to create an action document that can be transmitted directly to the location or person responsible for supplying the required information.

Similarly, we previously had no automated means to compare actual staffing with budgeted staffing in retail locations. To gather the required data, the store managers had to fax weekly a list of their current actual staffing to corporate recruiting. Following the receipt of the faxes, the data were collated, input into a spreadsheet, printed, and distributed. This data-gathering exercise was an extremely manual process that distracted store personnel from their primary focus-customer satisfaction.

The foundation of the HRMS system is ”position information.” Position information is needed to control staffing levels, and includes such information as types and numbers of staff positions that have been budgeted, new staffing needs, and salary ranges and grades. We defined each position with the company with the goal of reporting on the incumbent versus budgeted staffing levels. By developing an understanding of the needs of recruiting and store operations during the system implementation process, we were able to generate staffing reports that contain information on individual locations, regions, and the company for sales and store-support personnel. This single automated process annually saves some 4,000 processing hours.

Furthermore, by using the decision-support system, we are no longer restricted to developing staffing information on a weekly basis. During the most recent Christmas season, our recruiting manager produced the reports on a daily basis to efficiently direct recruiting resources to the locations in the greatest need.

At thegoodguys!, merit processing is performed three times per year. Previously, this was a semiautomated process that required line managers or human resources support personnel to devote weeks to completing the required paperwork. The use of the decision-support tool reduced the processing time of a merit cycle (the period during which candidates for merit increases are selected and evaluated for the level of a merit increase) by 30percent. It also eliminated the need for line managers to create action

Employment Relations Today Spring 1997 53

Tony Morgado

notices summarizing merit increases, and eliminated the need for HR representatives to input the changes. In addition, new reports have been created that give location managers salary and perfor- mance information that is used in the development and delivery of an associate’s review. Furthermore, the ability to integrate HR decision-support data with a custom modeling spreadsheet built in Microsoft Excel allows for extremely accurate forecasting of the impact of merit increases on payroll.

CREATING BUSINESS-ANALYSIS TOOL Although the HRMS can capture all the information that is

necessary in developing a business plan, and the decision-support tool is used to extract information that can be examined by business experts to identify trends, develop forecasts, devise possible solutions, and measure the impact of applied solutions, the business solutions are not in the software or hardware of the information system. The system can provide sales data, demo- graphic data on staff, and current and historic data on turnover rates, but it cannot tell you how to increase profits by 3,000 percent or how to reduce turnover or increase the product knowledge of sales associates. The data must be analyzed, and plans of action must be created, tested, and followed up. The greatest disservice to the organization would be to capture the data, extract the data, and place the data in a binder to collect dust.

One of our major goals was to create a business-analysis tool that would allow the integration of HR data with other data in the organization such as sales, finance, and payroll. During system implementation, it was clear that the integration of HR data with sales results was critical.

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We use the data to examine a number of business questions, including:

What are the sales productivity and return rates of part- time versus full-time sales associates? What is the impact of dedicated versus generalist sales associates? What is the impact of training solutions on sales productivity? What is the relationship between length of service and sales productivity?

These questions and many more have been asked, and the results have been shared with all levels of the organization: human resources, stores, finance, and operations.

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Prior to the implementation of HR Stream and its associated decision- support tool, we had no mechanism to verify the accuracy of the data.

An infinite amount of information can be provided through the use of a decision-support tool, but the information must be accessible by the reporting tool. A great amount of forethought must be given as to the types of questions that might be asked to ensure that the data are captured in the system and later extracted or accessed for analysis. The decision-support tool that is used to access the information can be selected as part of a new management system, but it may also be tied into an older system, with some modifications.

INCREASING DATA ACCURACY Because human resources is responsible for the collection of all

associate data, HR is also responsible for ensuring that the data are as accurate as possible. Yet, without a tool to review the data and verify accuracy, the best an HR department can do is attempt to input the data correctly and wait to hear from the auf,tors, associates, and managers regarding deficiencies and errors.

We are now in a position to efficiently ensure that we gather all required information on an associate: name, address, phone, social security, 1-9 (federal work authorization form), driver’s license, rate of pay, pay deductions, benefit elections, etc. And we can audit these items to ensure that the data captured are accurate based on the employment type, benefit eligibility, benefit elections, etc. Although data input errors are inevitable, we use a number of system warnings at the front end to catch invalid combinations of data. However, it is impractical to try to catch all possible errors at the front end of the process. Thus, we have used our decision-support tool to create a number of back-end audits (i.e., audits performed on a periodic basis to highlight invalid combinations of data).

Prior to the implementation of HR Stream and its associated decision-support tool, we had no mechanism to verify the accuracy of the data. For example, the benefit election and pay element information was input by the payroll department into the payroll system and by human resources representatives into the old human resources system, and there was no mechanism to compare the two systems. Today, we have an integrated HR and payroll system connected by a daily interface, and we regularly run audits to ensure that the information is the same for pay rates and deduction amounts. We also compare the benefit elections to benefit deductions to make certain that associates’ payroll deductions are appropriate for their deduction elections.

Along a similar line, the decision-support tool has allowed us to automate the delivery of benefit eligibility reports for our benefit carriers. We currently send our dental carrier an automated feed


Tony Morgado

w e now have hundreds of queries and reports that produce specific data for specific purposes.

that is posted in the carrier’s system within 72 hours. This is in contrast to the three weeks it previously took when a printed report was prepared and manually keyed by the benefit carrier. The result is obvious: an efficient delivery and guaranteed accuracy of the benefits eligibility list and better service for all in the organization.

ELIMINATING REDUNDANT DATA MANIPULATION Redundant data manipulation is the tell-tale sign that an HR

department must implement some sort of decision-support solu- tion. Redundant data manipulation refers to the process of rekeying report data into some other program, such as a spreadsheet, in an attempt to perform some analysis that the original report was not intended to support. It could mean taking multiple reports from different parts of the organization and using one column from each report and rekeying that information into a spreadsheet in an attempt to get some other analysis or a differently cast report. The ruinous aspect of this process is that the data must be rekeyed every time the source reports are changed, and individuals who are supposed to be supporting critical human resources functions are spending time rekeying data, making this an extremely expen- sive way to get poor-quality data.

With the decision-support system in place, we now have hundreds of queries and reports that produce specific data for specific purposes. Although it still takes time and effort to produce these reports, the payback is that the report is designed only once, and whenever the report is run, it can provide the most current information, using whatever combination of programmed data that is desired.

ENHANCING MANAGEMENT REPORTING One of our goals in the implementation and future develop-

ment of our human resources and decision-support tool is to expand our management reporting. Previously, it was often diffi- cult or impossible to fill all the requests for tracking information because the process was too labor-intensive. To say this has changed is an understatement. We now offer reports and analysis to all levels of the organization.

Prior to the implementation of the decision-support tool, our reporting on employee turnover was limited. We have redesigned and expanded the reporting and we now offer turnover information for all locations and position types as well as information on reasons for employment termination and length of service prior to termination. Store managers now receive monthly, detailed reports showing information on the specific individuals terminated from their location.



This allowed us to target procedures that could be streamlined with the aid of the decision-support tool.

In the past, we were unable to review the work history of any of our associates. Our decision-support tool has led to automated succession planning (i.e., promotion eligibility). For example, we can look at an associate’s progression through the management training program, duration with the company, and management positions held with the company. In the past, it took weeks to develop this information. Today, it is a matter of running a few predefined reports.

Similarly, we now produce reports showing the completion of required training. These reports are used to assist managers in guiding their staff through their required product and management courses.

These are a few examples of the types of reporting now supplied through our decision-support tool. Where we once con- ceded we could not capture or provide information, we are now able to offer data for various types of analysis.

SYSTEM PLANNING PROCESS A critical factor that has allowed us to maximize the power of

our decision-support tool was the careful consideration of the goals that we wanted to achieve with respect to the type of information that we wanted to track, the levels within the organization that had to be served, and the types of reports that we ultimately wanted to generate. We also considered the type of growth that was anticipated within the HR staffing; our goal was slow growth or no growth in this area.

With the assistance of our implementation partner, CDG & Associates, we employed a specific strategy during the implementation process. We collected all reports that were used by HR (though not all were necessarily produced exclusively for human resources) and held joint analysis and design sessions with as many department managers as possible. The purpose of these meetings was to define current reporting requirements as well as to create a wish list of reports. Perhaps most importantly, we summarized and prioritized our decision-support solutions. We also performed task analysis in order to clearly understand how business processes were performed. This allowed us to target procedures that could be streamlined with the aid of the decision-support tool.

This process resulted in the identification of

1. the data that must be captured in our database to meet the reporting requirements of the organization and

2. high-impact reporting that should be attacked first in order to provide business analysis and improve processing efficiency.


Tony Morgado

CONCLUSION Because the implementation of the decision-support tool oc-

curred simultaneously with the implementation of the new HR management system, we had an ideal situation to stir organiza- tional support and participation in the development process. This support is critical to developing a system that will support the goals of the entire organization.

The implementation of the decision-support system freed the human resources department from the burdensome manual processing of information. We measured our success by the reduced data-inputting backlog. We now have a system that allows HR professionals to develop queries and reports and to perform analyses by combiningtheir vocational expertise with the needs of the organization. Thus, the use of a powerful decision-support tool can play a role in transforming the HR function from a reactive record-keeping department to an empowered strategic business partner. +


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Improving HR leadership through effective decision support