February 10, 2022

PERFORMANCE APPRAISAL Performance appraisal is a process concerned with determining how well employees are doing their jobs, communicating that information to the employees and establishing a plan for performance improvement. Appraisal is the judgment of an employee’s performance in a job, based on consideration other than productivity atone.  What is being assessed in appraisal is the employee’s performance in carrying out the general duties of his/her role, together with any specific targets that have been set. Performance appraisal is the process of determining and communicating to an employee how he is performing on the job and establishing a plan of improvement.  They tell an employee how well he is performing and the future level of effort and took direction. Reasons for Performance Appraisal For making administrative decisions relating to promotions, firings, layoffs and merit pay increases. It helps a manager decide what increases of pay shall be given on grounds of merit. For determining the future use of an employee. Appraisal can provide needed input for determining both individual and organizational training and development needs, through identifying strengths and weaknesses. Appraisal encourages performance improvement. They may motivate the employee to do better in his current job due to knowledge of results, recognition of merit and the opportunity to discuss work with his manager. Appraisals help to identify an individual’s current level of performance. Information generated by appraisal can be used as an input to the validation of selection procedures. Appraisal information is an important input to human resource planning and succession planning, career planning and so on. By making effective use of the performance appraisal system, an organization may seek to: – Improve productivity Promote internal control through timely detection and feedback on actual performance Create a positive work environment Stimulate, recognize and reward achievements Provide objective measures of performance Furnish information for other HR sub-systems. Frequency of Performance Appraisal Despite the many potential benefits of appraisal, many organizations do not make effective use of the system.  When appraisal is infrequently used, employees voice concern about the possible abuse.  There seems to be no real consensus on how frequently performance appraisals should be done, but it is good to have them as often as in necessary to let employees know what kind of job they are doing, and measures to be taken for improvement. An annual appraisal is not enough.  For most employees informal performance appraisals can be conducted two or three times a year in addition to an annual formal performance appraisal. Key Principles in the design of Appraisal Schemes. Create motivation to change or improve behaviour. Provide recognition for successful performance. Provide valid and reliable information for pay decisions. Provide guidance on what skills, competences and behaviour are needed to meet expectations. Need to be simple, clear and written in accessible language. Must make realistic demands on employees and managers time and other resources. Must be perceived to be fair. PERFORMANCE APPRAISAL METHODS   Selection of a Performance Appraisal Method Whatever method of appraisal an organizational uses, it must be job related.  Therefore before selection of a method, an organization must conduct job analyses and develop job descriptions. Methods of Performance Appraisal Goal setting or Management by Objectives (MBO). Multi-rater (360 – degree feedback). Ranking methods. Rating methods. Work standards approach. Essay appraisal. Critical – incident appraisal. Checklist. Assessment centre. Open –ended method. GOAL – SETTING OR MANAGEMENT BY OBJECTIVES This is more commonly used with professional and managerial employees.  Other terminologies used for this include; management by results, performance management, results management and work planning and review programmes. The MBO process consists of the following steps:- Establishing clear and precisely defined statements of objectives for the work to be done by an employee. Developing an action plan indicating how these objectives are to be achieved. Allowing the employee to implementing the action plan Measuring objective achievement Taking corrective action when necessary Establishing objectives for the future. For MBO to be successful; Objectives should be quantifiable and measurable Objectives should be challenging yet achievable Objectives should be expressed in writing and in clear, concise, unambiguous language Employees should participate in the objective-setting process The objectives and action plan must serve as a basis for regular discussions between manager and employee

Performance Review & Development Meetings Both parties should prepare for the meeting so that they consider the points for discussion. Assess the achievement of objectives; understand the factors that affected performance and actions necessary to improve performance. Self-Assessment. The employee should consider achievements and progress, prepare to explain the shortfalls, training and development needs. Constructive Review Meetings Such a meeting is likely to take place if reviewers:- Encourage reviewees to do most of the talking Listen actively to what they say Allow scope for reflection and analysis Analyse performance, not personality Keep the whole period under review, not isolated incidents Adopt a ‘no surprises’ approach – performance problems should have been identified and dealt with at the time they occurred Recognize achievements and reinforce strengths End the meeting positively with agreed action plans and an understanding of how progress in implementing them will be reviewed.  Organizational characteristics. Emphasis on past clashes with managerial preference for current information No commitment to appraisal Conducting of appraisals not reinforced – no rewards PA not an important function of management. Redundant in participative democratic climate. Position characteristics. Inability to observe performance.   SYSTEM CHARACTERISTICS. Implementation No user participation in system development. Failure to develop performance measures from job analysis. Rating systems administered subjectively. Results used to discriminate on the basis of race, gender etc.  Performance appraisal policies. No standard policy regarding raters tasks/roles in appraisal. No standard policy regarding frequency of appraisals. PERFORMANCE APPRAISAL ELEMENTS. Rater and rating process Observation Lack of knowledge of ratees job. Possession of erroneous or incomplete information. Differing expectations because of levels in hierarchy and role  Judgement Bias and errors in human judgement. Stereotypes and prejudices. performance appraisal instrument. Performance measures (criteria) Ambiguity of performance measures: incompleteness. Lack of specificity and behaviour – based language Irrelevant performance criteria Criteria not communicated explicitly to ratees. PERFORMANCE APPRAISAL OUTCOMES.   Evaluation Failure to recognise excellent performance Promotional decision errors Staffing jobs with inadequate skills mix          Guidance and development. Failure to recognise potential Failure to build skills through training. Motivation. Grievances because of subjectivity and bias.

PERFORMANCE MANAGEMENT Definition This means the integration of employee development with results based assessment. It encompasses performance appraisal, objective setting for individuals and departments, appropriate training programmers and performance related pay. Performance management emphasis development and the initiation of self-managed learning plans as well as the integration of individual and corporate objectives. Performance management is a strategic and integrated approach to delivering sustained success to organizations by improving the performance of the people who work in them and by developing the capabilities of teams and individual contributors. Performance is a record of outcomes achieved. Performance management is a means of getting better results from the organization, teams and individuals by understanding and managing performance within an agreed framework of planned goals, standards and competence requirements. It is a process of establishing shared understanding about what is to be achieved, and an approach to managing and developing people in a way that increases the probability that it will be achieved in the short and longer term. Performance management is a broad process that requires managers to define, facilitate and encourage performance by providing timely feedback and constantly focusing everyone’s attention on the ultimate objectives. Principles Of Performance Management It translates corporate goals into individual, team, department and divisional goals It helps to clarify corporate goals It is a continuous and evolutionary process in which performances improves over time It relies on consensus and cooperation rather than control or coercion It encourages self-management of individual performance It requires management style that is open and honest and encourages two-way communication between superiors and subordinates It requires continuous feedback Feed back loops enable the experience and knowledge gained on the job and individuals to modify corporate objectives It measures and assess all performance against jointly agreed goals It should apply to all staff; and it is not primarily concerned with linking performance to financial rewards. Concerns of Performance Performance management is concerned with performance improvement in order to achieve organizational, team and individual effectiveness Performance management is concerned with employee development. Performance improvement is not achievable unless there are effectiveness process of continuous development Performance management is concerned with satisfying the needs and expectations of all the organizations stakes holders –owners, management, employees, customers, suppliers and the general public Performance management is concerned with communication and involvement. It may contribute to the development of a high-involvement organization by getting teams and individuals to participate in defining their objectives and the means to achieve them. Aims of Performance Management. Improve organisational effectiveness Motivate employees Improve training and development. Set objectives and targets of work Provide feedback on performance. Change the organisational culture.

Computer Security: Principles and Practice Classes of intruders: criminals • Individuals or members of an organized crime group with a goal of financial reward – Identity theft – Theft of financial credentials – Corporate espionage – Data theft – Data ransoming • Typically young, often Eastern European, Russian, or southeast Asian hackers, who do business on the Web • Meet in underground forums to trade tips and data and coordinate attacks Classes of intruders: activitists • Are either individuals, usually working as insiders, or members of a larger group of outsider attackers, who are motivated by social or political causes • Also know as hacktivists – Skill level is often quite low • Aim of their attacks is often to promote and publicize their cause typically through: – Website defacement – Denial of service attacks – Theft and distribution of data that results in negative publicity or compromise of their targets Intruders: state-sponsored • Groups of hackers sponsored by governments to conduct espionage or sabotage activities • Also known as Advanced Persistent Threats (APTs) due to the covert nature and persistence over extended periods involved with any attacks in this class • Widespread nature and scope of these activities by a wide range of countries from China to the USA, UK, and their intelligence allies Intruders: others • Hackers with motivations other than those previously listed • Include classic hackers or crackers who are motivated by technical challenge or by peer-group esteem and reputation • Many of those responsible for discovering new categories of buffer overflow vulnerabilities could be regarded as members of this class • Given the wide availability of attack toolkits, there is a pool of “hobby hackers” using them to explore system and network security Skill level: apprentice • Hackers with minimal technical skill who primarily use existing attack toolkits • They likely comprise the largest number of attackers, including many criminal and activist attackers • Given their use of existing known tools, these attackers are the easiest to defend against • Also known as “script-kiddies” due to their use of existing scripts (tools) Skill level: journeyman • Hackers with sufficient technical skills to modify and extend attack toolkits to use newly discovered, or purchased, vulnerabilities • They may be able to locate new vulnerabilities to exploit that are similar to some already known • Hackers with such skills are likely found in all intruder classes • Adapt tools for use by others Skill level: master • Hackers with high-level technical skills capable of discovering brand new categories of vulnerabilities • Write new powerful attack toolkits • Some of the better known classical hackers are of this level • Some are employed by state-sponsored organizations • Defending against these attacks is of the highest difficulty Intruders: another classification • Masquerader: unauthorized individuals who penetrates a system • Misfeasor: legit user who accesses unauthorized data • Clandestine: seizes supervisory control Example of intrusion • Remote root compromise • Web server defacement • Guessing/cracking passwords • Copying databases containing credit card numbers • Viewing sensitive data without authorization • Running a packet sniffer • Distributing pirated software • Using an unsecured modem to access internal network • Impersonating an executive to get information Intruder behavior • Target acquisition and information gathering • Initial access • Privilege escalation • Information gathering or system exploit • Maintaining access • Covering tracks

The measures of central tendencies (i.e. means) indicate the general magnitude of the data and locate only the center of a distribution of measures. They do not establish the degree of variability or the spread out or scatter of the individual items and their deviation from (or the difference with) the means. 1. According to Nciswanger, “Two distributions of statistical data may be symmetrical and have common means, medians and modes and identical frequencies in the modal class. Yet with these points in common they may differ widely in the scatter or in their values about the measures of central tendencies.” 2.Simpson and Kafka said, “An average alone does not tell the full story. It is hardly fully representative of a mass, unless we know the manner in which the individual item. Scatter round it …. a further description of a series is necessary, if we are to gauge how representative the average is.” Purpose To introduce the learner to various measures of disparity in a given set of data. From this discussion we now focus our attention on the scatter or variability which is known as dispersion. Let us take the following three sets. Thus, the three groups have same mean i.e. 50. In fact the median of group X and Y are also equal. Now if one would say that the students from the three groups are of equal capabilities, it is totally a wrong conclusion then. Close examination reveals that in group X students have equal marks as the mean, students from group Y are very close to the mean but in the third group Z, the marks are widely scattered. It is thus clear that the measures of the central tendency is alone not sufficient to describe the data. Definition of dispersion: The arithmetic mean of the deviations of the values of the individual items from the measure of a particular central tendency used. Thus the ’dispersion’ is also known as the “average of the second degree.” Prof. Griffin and Dr. Bowley said the same about the dispersion. In measuring dispersion, it is imperative to know the amount of variation (absolute measure) and the degree of variation (relative measure). In the former case we consider the range, mean deviation, standard deviation etc. In the latter case we consider the coefficient of range, the coefficient mean deviation, the coefficient of variation etc.

1. It should be rigidly defined 2. It should be easy to understand and calculate 3. It should be based on all observations 4. It should be amenable to further algebraic manipulation. 5. It should not be affected much by extreme values 6. It should be least affected by fluctuations in sampling.

1. It is ill defined. 2. It is not based on all observations. 3. It is not capable of further algebraic treatment. 4. It is not a good representative of the data. 5. Sometimes there are more than one values of mode.

1. It is simple to calculate. 2. In individual or discrete distribution it can be located by mere inspection. 3. It is easy to understand. Everyone is used to the idea of average size of a garment, an average American etc. 4. It is not isolated like the median as it is the most common item. 5. Like the Average mean, it is not a value which cannot be found in the series. 6. It is not necessary to know all the items. What we need the point of maximum density frequency. 7. It is not affected by sampling fluctuations.

1. It is rigidly defined. 2. It is easy to calculate and understand. 3. It is not affected by extreme values like the arithmetic mean. For example, 5 persons have their incomes $2000, $2500, $2600, $3000, $5000. The median would be $2600 while the arithmetic mean would be $3020. 4. It can be found by mere inspection. 5. It is fully representative and can be computed easily. 6. It can be used for qualitative studies. 7. Even if the extreme values are unknown, median can be calculated if one knows the number of items. 8. It can be obtained graphically.

1. It is rigidly defined. Its value is always definite. 2. It is easy to calculate and easy to understand. Hence it is very popular. 3. It is based on all the observations; so that it becomes a good representative. 4. It can be easily used for comparison. 5. It is capable of further algebraic treatment such as finding the sum of the values of the observations, if the mean and the total number of the observations are given; finding the combined arithmetic mean when different groups are given etc. 6. It is not affected much by sampling fluctuations

A single value which can be considered as typical or representative of a set of observations and around which the observations can be considered as Centered is called an ’Average’ (or average value) or a Centre of location. Since such typical values tend to lie centrally within a set of observations when arranged according to magnitudes, averages are called measures of central tendency. Purpose To examine various measures of central tendency. In fact the distribution have a typical value (average) about which, the observations are more or less symmetrically distributed. This is of great importance, both theoretically and practically. Dr. A.L. Bowley correctly stated, “Statistics may rightly be called the science of averages.” The word average is commonly used in day-to-day conversations. For example, we may say that Okanga is an average boy of my class; we may talk of an average American, average income, etc. When it is said, “Okanga is an average student,” it means is that he is neither very good nor very bad, but a mediocre student. However, in statistics the term average has a different meaning. The fundamental measures of tendencies are: (1) Arithmetic mean (2) Median (3) Mode (4) Geometric mean (5) Harmonic mean (6) Weighted averages However the most common measures of central tendencies or Locations are Arithmetic mean, median and mode. We therefore, consider the Arithmetic mean.

Primary data is data that you collect yourself using such methods as: direct observation – lets you focus on details of importance to you; lets you see a system in real rather than theoretical use (other faults are unlikely or trivial in theory but quite real and annoying in practice) surveys – written surveys let you collect considerable quantities of detailed data. You have to either trust the honesty of the people surveyed or build in self-verifying questions (e.g. questions 9 and 24 ask basically the same thing but using different words – different answers may indicate the surveyed person is being inconsistent, dishonest or inattentive). interviews – slow, expensive, and they take people away from their regular jobs, but they allow in-depth questioning and follow-up questions. They also show non-verbal communication such as face-pulling, fidgeting, shrugging, hand gestures, sarcastic expressions that add further meaning to spoken words. e.g. “I think it’s a GREAT system” Purpose To introduce the student to some basic techniques of collection of data. could mean vastly different things depending on whether the person was sneering at the time! A problem with interviews is that people might say what they think the interviewer wants to hear; they might avoid being honestly critical in case their jobs or reputation might suffer. logs (e.g. fault logs, error logs, complaint logs, transaction logs). Good, empirical, objective data sources (usually, if they are used well). Can yield lots of valuable data about system performance over time under different conditions. Primary data can be relied on because you know where it came from and what was done to it. It’s like cooking something yourself. You know what went into it. Secondary data is collected from external sources such as: TV, radio, internet magazines, newspapers reviews research articles stories told by people you know There’s a lot more secondary data than primary data, and secondary data is a whole lot cheaper and easier to acquire than primary data. The problem is that often the reliability, accuracy and integrity of the data is uncertain. Who collected it? Can they be trusted? Did they do any preprocessing of the data? Is it biased? How old is it? Where was it collected? Can the data be verified, or does it have to be taken on faith? Often secondary data has been pre-processed to give totals or averages and the original details are lost so you can’t verify it by replicating the methods used by the original data collectors. In short, primary data is expensive and difficult to acquire, but it’s trustworthy. Secondary data is cheap and easy to collect, but must be treated with caution.