Consultation Competency Flashcards
(29 cards)
Role of HR in Managing Change
Identify programs, practices, and policies that might benefit from change.
Identify the impact of the change on people and departments, which may include gaps in skills, lines of communication to be opened, and new policies that may be required.
Assess the impact of changes across the organization and also on outside stakeholders—the ripple effect of change.
Consult with the organization’s leaders on ways to support the change initiative, including changes in organizational culture (for example, different approaches to decision making), new processes (for example, reward systems aligned with the new behaviors), and investment in learning and development to support employees as they develop new competencies to perform their changed roles.
Use communication skills and channels to contact all affected stakeholders quickly and uniformly, communicate the details of the change initiative, and keep them apprised of developments and progress. Effective communication during periods of change can produce:
Identification and mitigation of potential risks.
Increased management and employee buy-in and satisfaction.
Increased trust between management and nonmanagerial employees.
Identification of needed change-related training initiatives to improve employee skills and proficiency throughout the change process.
Increased leadership cohesiveness.
Measure the effectiveness of the change initiative.
Track issues that arise at any point and follow up to deliver superior service to HR’s internal customers.
J curve
Employee productivity and engagement can be affected by both large shifts in culture, structure, and strategic goals and small changes in roles and processes. This effect is often referred to as the “dreaded J curve,” shown in Exhibit 1-42. When change is introduced, there is typically a decline in performance and then a slow return to previous levels and—if the change is effective and if it is managed effectively—a more rapid growth to a new level of performance. A poorly chosen intervention or poor management of the change process can result in a more permanent flattening of the curve at a low plateau, as indicated by the dotted line.
To manage the negative effects of change on productivity
Some may resist change, driven perhaps by fear of the unknown or a lack of confidence in their ability to perform new tasks. They may prefer inertia and the comfort of the familiar to the challenge of learning new roles and skills.
Some employees will welcome the change because they can immediately see its benefits (for example, improved communication, more individual control).
Others may simply be waiting for more information to decide how they feel.
The key to managing change
to recognize these reactions promptly and respond appropriately. Resistant employees, for example, can derail a change initiative quickly if their attitudes are allowed to affect other team members.
For employees resisting changes, managers must make a special effort to listen to their fears and doubts, to check in frequently, and to offer additional resources to help them adapt to new processes or structures. Managers can also emphasize the benefits that outweigh the costs of change. If an individual’s attitude becomes harmful to the group, the manager may have to emphasize new expectations and the employee’s obligation to meet them.
Managers can use more receptive employees as champions of the changes, communicating their reasons and their enthusiasm to their peers.
For employees who have not committed to or have rejected the change, managers may have to sell the potential benefits—both organizational and personal—of the change. Managers can also assign them tasks or roles to increase the level of their involvement in the process.
A model developed by John Kotter (Leading Change)
provides insight into the “how” of the change management process by specifying eight contributors to successful implementation of the change:
Create a sense of urgency.
Assemble a strong guiding team.
Provide a clear vision.
Over-communicate.
Empower action.
Ensure short-term successes.
Sustain progress and build on achievements.
Institutionalize.
Force-field analysis
tries to identify conditions needed to make change possible. Based on a force-field analysis, the group can decide to pursue opportunities with scores showing favorability for change or avoid changes that face very strong resistance. They might also use analysis results in deciding how to allocate resources to mitigate negative risks and enhance opportunities.
six steps described by Ben Eubanks,
Ask. When faced with a problem, translate the situation into a question that can then be answered through information gathering. For example, an HR manager notes that the discipline system the organization uses is not effective in preventing eventual terminations or resignations. The HR manager asks, “What are we doing now? Does our disciplinary approach reflect what we know about adult behavior and motivation to change?”
Acquire. Gather information from varied sources. For example, the HR manager reviews the organization’s policies and processes concerning discipline and retrieves from HR’s records data about disciplinary actions and subsequent employee history. The HR manager develops some case studies on specific incidents, gathering information from the supervisors involved. The manager also begins to gather information about current research into these areas and assessments of current practices from journals and HR professional societies and networks.
Appraise. Determine whether the evidence gathered is relevant, valid, reliable, accurate, complete, and unbiased.
Aggregate. Combine and organize the data to prepare it for analysis. Determine the priority to be given to different types of information.
Apply. See the logical connections within the data and with the issue. Use the data to draw conclusions, develop possible solutions, win sponsor support for a decision, and take action.
Assess. Monitor the solution that has been implemented and objectively measure the extent to which the objectives have been attained.
focus group
is a small group (normally six to twelve) invited to actively participate in a structured discussion with a facilitator. Focus groups typically last from one to three hours, depending on the topic and the purpose. Focus groups serve a variety of purposes. They are often used to follow up on a survey, providing a more in-depth look at specific issues raised during the survey. In this respect, focus groups collect qualitative data that enriches quantitative survey results.
When planning a focus group, HR professionals should consider the following.
The importance of planning. Effective planning is critical. Focus group objectives must be clearly defined, as they influence all subsequent focus group questions and the structure and flow of the discussion. Any stimulus materials should be designed and debugged in advance.
The context in which a focus group might occur. Cultural effects, both organizational and national, could affect participation, and legal environments could affect the information gathered.
The importance of the facilitator. Similar to planning, having a good facilitator (or moderator) contributes to a successful focus group. A focus group facilitator should:
Know the topics reasonably well.
Be a good listener.
Possess a good understanding of group dynamics and skill at conflict resolution (should differences in opinions arise).
Allow group perspectives to emerge without interjecting any bias or allowing any one individual to dominate.
Have enthusiasm for the session (which can be contagious in a group setting).
Possess competent facilitation skills for any focus group activities and exercises.
Be conscious of time allocation and usage.
If the organization does not have qualified staff to act as facilitators, it could consider hiring an outside facilitator who possesses the characteristics listed above.
The importance of the recorder. A focus group should have a person designated as a note taker to record comments on flip charts, etc. A designated note taker allows the facilitator to remain focused on group dynamics that enrich the focus group experience.
Serious challenges with technology
Obtaining a valid sample. Researchers must make sure that survey results are truly representative—that the number of returned surveys is sufficiently large to be representative and that the group responding accurately reflects the attributes of the entire group. Explaining the purpose and importance of the survey may improve the response rate, as will making it easier to complete—shorter and easier to understand. Researchers should be aware of survey approaches that affect who can respond—for example, using an online survey in a workplace where not all workers have equal online access. This affects the sample size and the ethical impact of the survey.
Designing the survey with analysis in mind. Questions should be asked in a way that makes compiling and comparing responses easier. This usually means relying heavily on quantifiable responses (for example, the Likert scale, which asks respondents to choose ratings, usually from 1 to 5 points). Freeform feedback (narrative comments, examples, suggestions) can be included as well and will enrich the research report.
Asking the right questions. To understand an entire organization, experts often turn to questions based on organizational models that map various internal and external environmental factors that can affect attitudes and work. Internal factors generally include strategy and purpose, leadership, rewards, and relationships; external factors include opportunities and threats as in SWOT and PESTLE analyses. In global or diverse organizations, researchers must also be mindful of language and cultural differences that could complicate the communication task.
Reliability
reflects the ability of a data-gathering instrument or tool, such as a survey or a rater’s observation or a physical measurement, to provide results that are consistent.
Validity
is the ability of an instrument to measure what it is intended to measure. Validation answers two questions:
What does the instrument measure?
How well does the instrument measure it?
Sampling
is often used when the population to be analyzed is very large or when data cannot be obtained from the entire population. The sample must be representative; it must accurately reflect the key characteristics of the entire population being studied. For example, the sample used in a wage survey of employees in a certain job should include the same ratio of genders and years of experience as for all employees in that job. Samples of data must also be sufficiently large to include all the possible variations within the population being sampled. The smaller a sample is, the more likely analysis results will be affected by statistical outliers, values that differ greatly from the average. This is a common problem with surveys with low response rates.
median
or 50th percentile, is the middle value in a range of values. The median is the preferred measure of central tendency when the distribution in a dataset is skewed—when it contains a few excessively high or low values. It is also used in frequency distributions, which are described elsewhere.
mode
is the most frequently occurring value in a set of data.
unweighted mean
or raw average, is the sum of all the values in the sample divided by the number of values. This is useful when all the values are relatively close together and when they represent volume as opposed to numerical order or numerical preference. For example, a group of ten employees in a particular position are surveyed to see how much time they spend on job tasks. The employees’ answers are only slightly different for one task: the largest number is 60 minutes a day and the smallest is 50 minutes. The unweighted average provides a useful gauge in answering a job seeker’s question, “How many hours a day would I be doing X?”
weighted mean
or weighted average, is used when some data in the dataset have more significance or effect than other data. In the salary example, there are two challenges in relying on an unweighted average for a better picture of salaries across the organization. First, there is a relatively large spread between the highest and lowest values—$20,000, or almost 40% of the salary in Division A. Second, there are significant differences among the divisions. Only two employees receive $55,000 in Division A, but five employees receive $70,000 in Division D.
Standard deviation
represents the distance of any data point from the center of a distribution when data is distributed in a “normal” or expected pattern. This is often shown as a bell curve. In a normal distribution, 68% of data lies within one standard deviation (expressed often as SD or the Greek letter sigma [σ]), 95% of data lies within two SDs, and 99% lies within three SDs.
Variance analysis
identifies the degree of difference between planned and actual performance. The term is usually applied to analysis against objective baselines, such as schedules and budgets. Once identified, different analytical tools, such as those described below, can be applied to understand the variance.
Ratio analysis
compares the relative size of two variables and yields a percentage. Net profit margin, for example, is a ratio that compares net revenue with costs. Many commonly used HR metrics are ratios, such as the turnover rate (comparing the number of terminations or resignations in a time period with the average number of employees in that period).
trend analysis
examines data from different points in time to determine if a variance is an isolated event or if it is part of a longer trend. By establishing the direction and degree of change over time, the trend analysis can also be used to forecast future conditions, such as the ability of an initiative to meet its objectives. Both trend analysis and forecasting can be performed within software applications. Trend analyses are important tools in discovering recurring peaks or troughs in an activity. For example, HR can use trend analysis to identify the most appropriate times to conduct campus job fairs by tracking the results from events held at different times over multiple years.
Regression analysis
refers to a statistical method used to determine whether a relationship exists between variables and the strength of the relationship. Data points can be plotted on a diagram called a scattergram. The shape of the line formed by the data suggests if there is a likely correlation, whether that correlation is positive or negative, and how strong or weak the correlation is. Analyses can use multiple variables.
Root-cause analysis
starts with a result and then works backward. Each cause is queried to identify a preceding cause—conditions or actions that might have led to this effect. This questioning may proceed backward in rounds until the fundamental or root cause is identified—the point at which no further causes can be identified. This method is sometimes referred to as the “five whys method,” which was developed as part of the Toyota Industries quality initiatives.
scenario/what-if analysis
can be used to test the possible effects of altering the details of a situation to see how the outcomes will vary under different conditions. The outcome of a particular situation is projected, using different inputs to see what changes have the most profound effects. This analysis is greatly aided with software applications and models. Monte Carlo analyses, for example, use computing capabilities to change scenario variables randomly and thereby generate up to thousands of possible outcomes. This can be helpful when analysts fear that historical patterns may not hold in the future.
