Lean Quality Management Example

GE Money Case Study

The author of this report has been asked to answer to the case study of either GE Money or Avon Products from the Goldsmith and Carter textbook. The author of this report chose the former rather than the latter. To that end, the author of this report will first give a list of the problems that GE Money discovered and decided needed to be rectified. Second, the author of this report will identify the model of change theory that is typified in the case study for GE Money. Third, there will be an illustration of the types of evaluation information that were collected and how they were used to benefit the company being analyzed. Fourth, there will be a speculation about the success of the changes within the next five years and how adjustments could be made if the changes do not reveal an ideal amount (or type) of change or changes. During the course of this assignment, the author will use at least five quality academic sources.

Analysis

The case study mentions four overall challenges that were found and discovered by GE Money. First, there was a lack of advertising budget management and overall tracking of spending associated with the same. Second, there was an inconsistent process across all of the client locations in question. Third, there was a lack of resources to research the best ways to advertise and reach the desirable target candidates. This would include cutting-edge technology and emerging trends in the greater human resources and recruiting sphere. Finally, there was not tracking of return-on-investment (ROI) as it related to cost per hire. In other words, there was not a comparison between the cost per hire and the net benefits reaped from the same hires. The prescribed remedy was a "comprehensive" or "long-term solution" and neither was apparently in existence at the time. The solution GE Money came up with centers on the use of dedicated headhunters that actually end up costing the company less than the prior method. Facets of that solution included shared services recruiters, an off-site sourcing engine, leveraged sourcing tools, expert sourcing knowledge, the heavy use of subject matter experts (SME's), accountability to metrics and service level agreements (SLA's) and reduced reliance on search firms. Indeed, the case study itself shows that costs related to search firms plummeted from 2005 to 2007. In 2005, the overall costs were $5.3 million. In 2006, that number dropped by about a fifth to $4.2 million. The number then dropped another whopping 79% from 2006 to 2007 when it fell to $1.3 million (Goldsmith & Carter, 2010).

As directly mentioned by the case study itself, the basic change model that the GE Money people used was the "work smarter, not harder" approach. Rather than throwing money at the problem and thus probably making the situation worse (if not MUCH worse), they analyzed how to move forward using a leaner and more streamlined approach that led to great results with less money spent on methods that were ineffectual or inefficient. The way they did that is through a lean quality management reviews and the use of kaizen teams, as described just below figure 6.4 in the case study. They did a top-to-bottom review and looked at the value (or lack thereof) of their current methods and the potential alternatives and they came to some methods that got the results they wanted but with a much better return on investment and less overall money spent. Indeed, to have overall search firm costs drop by roughly eighty percent from its peak in 2005 is nothing short of astonishing and this is especially true if SLA's, metrics and accountabilities all surged ahead at the same time. In terms of the types of evaluation information that were used, they assessed what was wasteful, what could be done to improve production and what could be done to improve quality. More specifically, they sought ways to increase quality while not necessarily spending as much as would be necessary with other methods. Indeed, the results of any given method matter but the amount of money spent per hire matters as well. As an example, if $10 million is spent on a "scorched earth" method with a lot of resources used and one thousand good applicants are found, it is indeed true that one thousand applicants were fettered out but $10,000 was spent per hire. That is no small sum of money. However, if the work of finding those applicants can be streamlined, targeted and simplified and the same number of applicants can be hired for a total of $1 million, the amount spent per hire has fallen by ninety percent and the return on investment will certainly be a lot hire. In the former case, it could very well be negative if the hire turns out to be a bust. The author of this report infers all of this basically from the verbiage of the case study itself. What is being said in no uncertain terms was that the prior methods of recruiting were technically operational but they were being done in different fashions from location to location and the overall efficiency was less than desirable. Indeed, they have since shifted to a single and unified process that is much more effective and has less operational costs involved because there is little to no variance from location to location. Inefficient and disparate practices should never be the norm at a top-end firm unless the actions and tasks involve require such inefficacy. Of course, that is simply not true of recruiting or human resources in general when it comes to most things so the prior process absolutely needed to be done away with (Goldsmith & Carter, 2010).

The author of this report is asked to conclude the report with how the success of the changes (or lack thereof) could guide the firm in the coming years and what could or should be done in response to those changes resulting in events that are less than what is expected or needed. Personally, the author of this report can see a few potential pitfalls and issues with the methodology that is being described in this case study but they can indeed be easily avoided. First of all, while variance in procedures and practices office to office and from location to location are normally less than optimal and preferable, there are times and situations where variance is required or preferential. For example, the laws surrounding human resources and business operations in general are not the same from state to state and especially not the same from country to country. Operating a business in Texas is an entirely different paradigm than operating a business in California. This is true in many respects that involve human resources including discrimination laws, benefit regulations, minimum wage rules and so forth. To use an example that can be directly applied to this case study, let one assume that the subject is compensation. When it comes to compensation, there are distinct and major regional variances when it comes to who is paid what and why and a lot of it depends on location just as much (if not more) than on what the job entails. For example, $70,000 is a good salary in a state like Kansas or even Texas. However, in a state like California, it is not nearly as much as it sounds like. Indeed, there are many cities in California where cost of living is extremely high and retaining good talent in those areas requires adjusting for those cost of living differences because any firm with a brain is already doing so. Surely, GE Money is using talent and resources that take that into account. However, if they are not doing so they will pay a heavy price because they will miss out on talent due to not knowing the employment and societal landscapes of the areas that they are operating in. If GE Money finds itself with pay scales and ladders that are not acclimated and attuned to an area and/or the metrics they are using are out of date, they need to get back into phase with the market or markets in question (Jalbert, Chan & Chalbert, 2012).

Another, and yet similar, pitfall that GE Money could run into is not accounting for other societal and cultural variances that exist in operating areas. Many to most geographical areas of the United States are basically the same but there are most definitely some outliers. These outliers can require a shift in hiring and operating tactics by businesses that operate in those areas and GE Money is certainly not immune from that. In general, GE money should obviously follow the same general hiring patterns from area to area. However, there are some situations where this would be less than wise. For example, if an area in which GE Money has an office has a high Hispanic population, there is an extremely high likelihood that there will be a good number of people that either do not speak English or that prefer to speak Spanish. For that reason, there should be hiring focus on those that are bilingual. The hires, whether it be executives or regular folks, need not be Hispanic/Latino but for them to know the language that the customers are comfortable with would be a boon to GE Money and would show that they are sensitive to the cultural and societal needs of an area. If GE Money were to have an office, let us say, anywhere in Los Angeles or Miami, they would be foolish to not have a Spanish speaker on hand at all times. However, it would probably be mostly a non-issue in cities like Kansas City and Saint Louis. The point is that if GE Money encounters problems because they are not catering to the needs of a geographical area, they should alter their approach in those areas in ways that are sufficient to address and allay those concerns (Miller & Tucker III, 2013).

Another concern that GE Money may need to take very seriously and thus would be wise to account for up front rather than after the fact is the racial/diversity makeup of an area as compared to the people that are employed in that same area. For example, let us say that a city (or area of a metro city) is about forty percent black. This would be well above the national average, which is about thirteen to fifteen percent. However, if the racial makeup of a GE Money office in the area is only ten percent, that is a huge red flag. It could be innocuous and unintentional but the Equal Employment Opportunity Commission (EEOC) and other similar regulatory bodies at the state or local level would be less than impressed. If GE Money were to find itself in such a situation, they would need to resolve this in a number of ways. First, they need to make very sure that there is a strong causality and association between the statement requirements or applicants that apply with GE Money and whether/how those requirements correlate with future success once a person is hired. If there are one or more requirements that are not easily linked to future job performance. Further, if the job applicant requirements in question tend to exclude a disproportionate amount of black or other minority applicants, then that is even worse. This is what is known in the human resources and equal employment opportunity "world" as disparate impact. If a hiring or interviewing process tends to lead to the exclusion of minority or female applicants being hired, then there is a hard analysis of whether the exclusion is the least bit intentional and/or whether the requirements in question are relevant to the job and the performance of selected hires. A historical example would be intelligence quotient (IQ) tests. These tests were commonly used in prior generations to measure the mental acuity of applicants and people that scored higher were obviously more likely to get hired. However, there are also the facts that IQ is not a reliable predictor of job success in many instances and blacks (just as one example) tended to score more poorly on such tests. Further, some businesses knew that full well and used those tests for precisely that reason. Obviously, a lot has changed since that practice was used and condoned but the general concept of disparate impact is still used to this day. As for what GE Money should do if they find they have an office in a high Latino or high-black area and their workforce at that location does not reflect that, they really need to take a hard look at why precisely that is the case and make adjustments as needed. This does not mean that they should accept more shoddy applicants just to keep the EEOC at bay. However, they also do not want to be deemed racist or prejudiced. Even the appearance or perception of such prejudice can be very dangerous for a firm even if there is no malfeasance and/or bad intent in play. In short, GE Money just needs to be sure that the proverbial playing field is level and that it is not excluding the wrong applicants (Miao, 2014; Kim, 2015).