1. Slide 1.1 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Chapter 1 Basic concepts – understanding information

2. Slide 1.2 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Learning objectives After this lecture, you should be able to: –distinguish between data, information and knowledge; –describe and evaluate information quality in terms of its characteristics; –classify decisions by type and organisational level; –identify the information needed to support decisions made at different organisational levels.

3. Slide 1.3 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Management issues From a managerial perspective, this chapter addresses the following areas: –the importance of managing information and knowledge as a key organisational asset; –the transformation process from data to information of high quality; –the process and constraints of decision making; –the different kinds of decisions that managers make and how these affect the organisation.

4. Slide 1.4 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Where is the emphasis? Where should it be? Information Technology The stress should be on the ‘I’ rather than the ‘T’ in ‘IT’ (Davenport, 2000). Peter Drucker stressed the importance of information to organisational competitiveness in 1993 when he wrote: ‘The industries that have moved into the center of the economy in the last forty years, have as their business, the production and distribution of knowledge and information rather than the production and distribution of things’.

5. Slide 1.5 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 What is data? Data are raw facts or observations that are considered to have little or no value until they have been processed and transformed into information. Example definitions: (a) a series of non-random symbols, numbers, values or words; (b)a series of facts obtained by observation or research and recorded; (c)a collection of non-random facts; (d)the record of an event or fact.

6. Slide 1.6 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 What is information ? Information: Data that have been processed so that they are meaningful. Example definitions: (a)data that have been processed so that they are meaningful; (b)data that have been processed for a purpose; (c)data that have been interpreted and understood by the recipient.

7. Slide 1.7 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Figure 1.1 Transforming data into information using a data process

8. Slide 1.8 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Information – summary Information: involves transforming data using a defined process; involves placing data in some form of meaningful context; is produced in response to an information need and therefore serves a specific purpose; helps reduce uncertainty, thereby improving decision behaviour.

9. Slide 1.9 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Activity What types of information processing are involved when a national retailer summarises national sales formation nationally?

10. Slide 1.10 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Types of information processing Classification: This involves placing data into categories, for example, categorising an expense as either a fixed or a variable cost. Rearranging/sorting: This involves organising data so that items are grouped together or placed into a particular order. Employee data, for example, might be sorted according to last name or payroll number. Aggregating: This involves summarising data, for example, by calculating averages, totals or subtotals. Performing calculations: An example might be calculating an employee’s gross pay by multiplying the number of hours worked by the hourly rate of pay. Selection: This involves choosing or discarding items of data on the basis of a set of selection criteria. A sales organisation, for example, might create a list of potential customers by selecting those with incomes above a certain level.

11. Slide 1.11 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Activity 1.1 – data versus information From the point of view of a student at university, which of the following might be examples of information? Which might be examples of data? –(a)the date –(b)a bank statement –(c)the number 1355.76 –(d)a National Insurance number –(e)a balance sheet –(f)a bus timetable –(g)a car registration plate

12. Slide 1.12 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Information value Tangible value: Value of info – Cost of gathering info Intangible value: Improvements in decision behaviour – Cost of gathering information

13. Slide 1.13 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Activity 1.2 Tangible and intangible information When information is used effectively, it can bring about many of the improvements listed below. State and explain why each of the items listed illustrates a tangible or intangible value of information. (a)improved inventory control; (b)enhanced customer service; (c)increased production; (d)reduced administration costs; (e)greater customer loyalty; (f)enhanced public image.

14. Slide 1.14 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 What is the importance of informal information? Formal communication: Formal communication involves presenting information in a structured and consistent manner. Informal communication: This describes less well-structured information that is transmitted by informal means, such as casual conversations between members of staff.

15. Slide 1.15 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Information quality dimensions

16. Slide 1.16 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Figure 1.2 The business environment of an organisation and the main factors that influence it

17. Slide 1.17 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 What is the relation between e-business and IT When a business has fully integrated information and communications technologies (ICTs) into its operations, potentially redesigning its business processes around ICT or completely reinventing its business model … e-business is understood to be the integration of all these activities with the internal processes of a business through ICT. DTI Definition

18. Slide 1.18 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 How does information support managers? Henri Fayol (1841–1925) devised a classic definition of management that is still widely used in both industry and academia. ‘To manage is to forecast and plan, to organise, to command, to coordinate and to control’

19. Slide 1.19 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Different decision types Decision behaviour: Describes how people make decisions and the factors that influence them. Structured decisions: Situations where the rules and constraints governing the decision are known. Unstructured decisions: Complex situations, where the rules governing the decision are complicated or unknown. Cognitive style: This describes the way in which a manager absorbs information and reaches decisions. A manager's cognitive style will fall between analytical and intuitive styles.

20. Slide 1.20 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Is your data hard or soft? Hard data, also known as quantitative data, tend to make use of figures, such as statistics. Hard data are often collected in order to measure or quantify an object or situation. Soft data, often known as qualitative data, tend to focus on describing the qualities or characteristics of an object or situation. Interviews, for example, are often used to collect qualitative data related to a person’s opinions or beliefs.

21. Slide 1.21 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Decisions and management level

22. Slide 1.22 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Figure 1.3 Levels of managerial decision taking

23. Slide 1.23 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Information characteristics by management level

24. Slide 1.24 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 A model of decision making

25. Slide 1.25 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Business rules Business rule: A rule that defines the actions that need to occur in a business when a particular situation arises. For example, a business rule may state that if a customer requests credit and they have a history of defaulting on payments, then credit will not be issued. A business rule is broken down into an event that triggers a rule with test conditions that result in defined actions.

26. Slide 1.26 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Figure 1.4 Decision tree notation for checking credit

27. Slide 1.27 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Figure 1.5 Framework for a decision table

28. Slide 1.28 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Figure 1.6 Decision table for the credit checking example

29. Slide 1.29 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Knowledge management The European Guide to Best Practice in Knowledge Management defines knowledge as: ‘The combination of data and information to which is added expert opinion, skills and experience to result in a valuable asset which can be used to make decisions. It is the essential factor in adding meaning to information. Knowledge may be explicit and/or tacit, individual and/or collective’ Mekhilef et al., 2003

30. Slide 1.30 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Competitive intelligence The Competitive Intelligence handbook (www.combsinc.com) presents different definitions of CI, for example: The objective of competitor intelligence is not to steal a competitor’s trade secrets or other proprietary property, but rather to gather in a systematic, overt (i.e., legal) manner a wide range of information that when collated and analysed provides a fuller understanding of a competitor firm’s structure, culture, behaviour, capabilities and weaknesses.

31. Slide 1.31 Bocij, Chaffey, Greasley, Hickie, Business Information Systems, 3 rd Edition © Pearson Education Limited 2006 Activity 1.8 Competitive intelligence and customer knowledge The marketing department of a construction company is planning the creation of a competitive intelligence system. Its aim is to capture and disseminate information about 30 key competitors and also existing or potential customers served by account representatives. You are designing the system. Working in groups, agree on an approach for: 1.Capturing data (who is involved, what information they need to collect). 2.Entering data (who is responsible for this, how they evaluate and categorise the different types of information entered). 3.Output requirements. Using the framework for quality of information in Table 1.1, what are the requirements in terms of types of content, frequency, who can access the data and filtering according to different criteria? 4.What types of hardware and software may be required for the system (reference to later chapters may be needed to answer this)?