1 IRU Data versus information Geoff Leese Sept 2001, revised Sept 2002, Sept 2003, August 2008, October 2009

2 Objectives n Understand importance of information to management n Distinguish between data and information n Know how data are transformed into information n Understand how information creates value n Define the characteristics of good information n Begin to understand the problems of perception

3 Importance of information n Coping with change, complexity and uncertainty n Operations rarely observed directly n Information obtained by ä Formal means ä Informal means

4 The value of information

5 Information - functions n Reduction of uncertainty n Aid to monitoring and control n Means of communication n Memory supplement n Aid to simplification

6 Categories of information n Strategic-long-term planning, imprecise, largely external. “Soft”. n Tactical-medium-term e.g. departmental sales forecasts n Operational-short-term, immediate goals, largely internal, precise. “Hard”

7 Levels of information n International information, n National information, n Corporate information, n Departmental information, n Individual information,

8 Relevant information n Increases knowledge n Reduces uncertainty n Is usable for intended purpose n Depends on many things ä Level of management, task in hand, urgency, confidentiality etc..

9 Data and information defined n Facts, events, transactions etc which have been recorded. They are the input raw materials from which information is produced. n Data that have been processed in such a way as to be useful to the recipient.

10 Information classification n By Source - internal, external etc. n By Nature - quantitative, qualitative etc. n By Level - strategic, tactical, operational n By Time - historical, present, future n By Frequency - continuous, hourly, daily etc. n By Use - planning, control, decision making. n By Form - written, aural, visual etc. n By Occurrence - planned intervals, on demand. n By Type - detailed, summarised, aggregated.

11 Characteristics of “good” information n relevant to purpose ä Up to date? ä “Unique”? ä Consistent? n accurate enough for purpose ä How do we measure this? n complete enough for purpose ä Is that ever possible? n user has confidence in source n communicated to right person in time for purpose n contains right level of detail n appropriate channel of communication used n understandable by user

12 Perception and Language n People see what they want to see! n Language simplifies things n What does “profit” mean? n Technical terms!

13 Problems with numeric data n Missing key data - not collected n Poor/incomplete measurement techniques n Subjective errors n Inappropriate methods n Poor presentation of results n Inaccuracy and misconceptions

14 At the design stage n Uniqueness ä Primary keys? n Consistency ä Foreign keys and referential integrity? ä Check constraints ä Triggers ä Dealing with unusual values n Completeness ä Dealing with null values ä Default values – use most common?

15 Management reports n Reports provide information for decision-making n based on data n underlying data stored in a database n extracted by software e.g. Reports

16 Types of management report n Analyses n Forecasts n Optimisations n Regular cyclical reports e.g. payroll n Exception reports n Decision support

17 Analyses n Summary e.g. sales figures last year n Should offer typical default reports n Should allow custom reports for specific data requirements n The higher the level, the less detailed and the more summarised the information

18 Forecasts & Predictions n Predictions take historical data and project the future on their basis, e.g. time series predictions n Forecasts based on subjective, conjectural data rather than historical data n The further into the future the forecast or prediction, the less reliable it is n Important not to get blinded by sophisticated mathematical techniques n Need to consider the assumptions made

19 Optimisation reports n Concerned with choosing the ‘best’ mix n Need to consider what is meant by ‘best’ n Optimising one factor is usually at the expense of other factors, e.g. time versus cost

20 Examples of optimisation techniques n Linear programming n Inventory modelling n Resource allocation techniques n Queuing theory n Simulation n Decision theory n e.g. Goal Seek in Excel

21 Exception Reporting n ‘No news is good news’ principle n ‘management by exception’ n how to decide what is exceptional? n parameters have to be continually reviewed

22 Decision support systems n Goal is to provide information to help decision-making n Best where there are a number of possible alternative actions n may include automated OR or statistical techniques n often built on database queries or expert-systems

23 Possible data storage locations n local database e.g. Access on desktop PC n LAN database n company-wide database n Intranet-closed n Internet-open

24 Reading n Kendall and Kendall (Systems Analysis and Design 5 th Edition) chapters 19 and 20 n Date chapter 19 (heavy stuff!) n An opinion on Data Quality – click to follow the link An opinion on Data Quality – click to follow the link