MATERI #5 Proses Diagnosa Informasi MISBAHUDDIN AZZUHRI SE. MM. CPHR®. CSRS®. 081 555 80 8899 081 233 72 8899 dinoazzuhri@live.com misbachazzuhri@gmail.com

Learning Objectives To understand the importance of diagnostic relationships in the OD process To describe the methods for diagnosing and collecting data To understand and utilize techniques for analyzing data To understand the importance of data feedback in the OD process To describe the desired characteristics of feedback content To describe the desired characteristics of the feedback process

OD’s 5 Stages

Diagnosing Problem Areas (part 1 of 2) Identification of areas for improvement. Assess current performance and desired level of quality. Provides information that allows for faster-reacting organization.

Diagnosing Problem Areas (part 2 of 2) Analyzes data on organization’s Structure. Administration. Interaction. Procedures. Interfaces. Other elements.

What is Diagnosis? Systematic approach to understand present state of organization. Specifies nature of problem and causes. Provides basis for selecting strategies. Involves systematic analysis of data.

Critical Issues in Diagnosis Simplicity Visibility Involvement Primary factors Measure what’s important Sense of urgency Critical Issues in Diagnosis

The Process Potential action programs. Data gathering. Identification of problem areas. Interpretation. Potential action programs.

Steps in Diagnosis Step 1: Step 2: Step 3: Step 4: Step 5: Step 6: Tentative problem identified Step 2: Collect data Step 3: Analyze data Step 4: Feedback data Step 5: More data needed Step 6: Problem areas identified Step 7: Is client motivated? Step 8: Diagnosis and work on problem Step 9: Monitor and assess results Steps in Diagnosis

The Diagnostic Relationship Who is the OD Practitioner? Why is the practitioner here? Who does the practitioner work for? What does the practitioner want and why? How will my confidentiality be protected? Who will have access to the data? What’s in it for me? Can the practitioner be trusted?

Data Collection - Feedback Cycle Planning to Collect Data Collecting Data Analyzing Data Feeding Back Data Following Up Core Activities

Data Collection Signs Signals Clues Facts Statistics Opinions Data is an aggregation of Signs Signals Clues Facts Statistics Opinions Assumptions Information is data that have form and structure.

Data Collection Stages Definition of objectives. Define objectives of change program. Identify preliminary diagnosis and further information required. Selection of factors. Identify central variables. May be necessary to increase range and depth of data. Selection of data-gathering method. Selection of one or more methods. Nature of the problem helps determine method. Variety of methods may be used.

Data Analysis Dictated by method used to gather data. Techniques used to analyze data. Dictated by method used to gather data. Type of analysis decided prior to data collection.

Guidelines for Evaluating Effectiveness of Data Collection Validity of data. Time to collect data. Cost of data collection. Organization culture and norms. Hawthorne effect in data collecting

Sampling Population vs. Sample Importance of Sample Size Process of Sampling Types of Samples Random Convenience

Questionnaires Major Advantages Major Potential Problems Responses can be quantified and summarized Large samples and large quantities of data Relatively inexpensive Major Potential Problems Little opportunity for empathy with subjects Predetermined questions -- no change to change Over-interpretation of data possible Response biases possible

Interviews Major Advantages Major Potential Problems Adaptive -- allows customization Source of “rich” data Empathic Process builds rapport with subjects Major Potential Problems Relatively expensive Bias in interviewer responses Coding and interpretation can be difficult Self-report bias possible

Observations Major Advantages Major Potential Problems Collects data on actual behavior, rather than reports of behavior Real time, not retrospective Adaptive Major Potential Problems Coding and interpretation difficulties Sampling inconsistencies Observer bias and questionable reliability Can be expensive

Unobtrusive Measures Major Advantages Major Potential Problems Non-reactive, no response bias High face validity Easily quantified Major Potential Problems Access and retrieval difficulties Validity concerns Coding and interpretation difficultie

Qualitative Tools Analysis Techniques Quantitative Tools Content Analysis Force-field Analysis Qualitative Tools Descriptive Statistics Measures of Association (e.g., correlation) Difference Tests Quantitative Tools

Force-Field Analysis of Work Group Performance Current Performance Desired Performance Forces for Change New Technology Better Raw Materials Competition from Other Groups Supervisor Pressures Forces for Status Quo Group performance norms Fear of change Member complacency Well-learned skills

Possible Effects of Feedback Feedback occurs No Change NO Is the energy created by the feedback? YES Energy to deny or fight data Energy to use data to identify and solve problems What is the direction of the feedback? Failure, frustration, no change Do structures and processes turn Energy into action? NO Anxiety, resistance, no change YES Change

Determining the Content of Feedback Relevant Understandable Descriptive Verifiable Timely Limited Significant Comparative Unfinalized

The Performance Gap* *) Difference between what organization could do and what organization is doing.

Self-Assessment Gap Analysis of Four Key Areas Organization’s strengths What can be done to take advantage of strengths Organization’s weaknesses What can be done to alleviate weaknesses

Effective Feedback Meetings People are motivated to work with the data The meeting is appropriately structured The right people are in attendance knowledge power and influence interest The meeting is facilitated

Survey Feedback Process Members involved in designing the survey The survey is administered to the organization The data is analyzed and summarized The data is presented to the stakeholders The stakeholders work with the data to solve problems or achieve vision

Limitations of Survey Feedback Ambiguity of Purpose Distrust Unacceptable Topics Organizational Disturbances

Case: OD Application Data Collection and Diagnosis at McDonald’s In ‘02 McDonald’s identified a problem based on earnings and profitability. Lack of data on customers prevented identifying problem. In ‘03 adopted system to gather data over long term. Data obtained from: Mystery diners who graded stores. In-depth interviews with customers. Data analysis showed solution: Deliver better experience for customers.

Managing Transitions | William Bridges Ending, Losing, Letting Go The Neutral Zone The New Beginning

Perceptions of Change |H. Woodward

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