Part - - -
In pairs, one person tells the other about their day (possibly yesterday). The person listening should write down only the information that is given as facts and figures, avoiding any context. For example you may state that you "got up at 7:20; it was a glorious day and the sun was streaming through the window." With the context removed this becomes "Got up at 7:20; sunny."
When you have finished, sap the notes you have taken with another pair. Each pair should try to recreate the other person's day.
As a group of four explain how the use of context improves the chances of effective communication.
Information is context, data is not.
The difference between data and information is context. The numbers 7, 11, 6 and 5 are on their own meaningless. They could refer to anything. However if the context is family shoe sizes, this provides some meaning to the numbers.
Data is information that has been coded and structured in some way, ready for processing, storage or transmission.
During research, when an interviewer asks a question, the answer is provided in the context of the question. This information from the answer is combined with the information from the other interviewees and is no longer the information about each of a series of individuals, instead it is information about a group of interviewees as a whole.
In this way the information becomes data again. For example the question may have asked people for their favourite fruit. Each individual answer was information but the collective answer 140 apples, 75 pears and 3 oranges is data; especially when option 1 was apples (and so 1 was recorded) in a multiple choice question.
In this way information becomes data ready for processing into "the bigger picture". Once it is processed and a new context applied it becomes new information.
3.2 Categories of information used by individuals
A simple e-mail home while on holiday, saying how your day has gone includes information. What you have sent is clearly information but other information that may range from comments about the weather to the fact that the e-mail was sent at 4:00 am local time are sent as well - possibly without the senders knowledge.
Education and training
Education and training generates a lot of information. We have already mentioned school reports, but could also talk about lists of grades provided to a student by a tutor. This could be paper based but could also be stored online in an intranet for example.
There are some superb films, but some are terrible. Websites such as IMDB and Rotten Tomatoes provide a synopsis of each film that they list as well as eventual scores based on the views of the people who have seen the film, These can be used to plan which films to watch.
It is worth noting that the score given to a film is based on the people who have seen it and so can change as more people submit their views. When a new film comes out, the first people to watch it are those who are most keen to see it; so their reviews are more likely to be positive than those without a special interest in the film. This is an example of bias.
Many people use shared electronic diaries to help them plan their lives. In a work context, these enable colleagues to arrange meetings on days when others are available, while members of a family can see what commitments individuals have and plan accordingly.
Banks and other organisations are able to provide us with a lot of information. Not only can they simply tell us how much money we have in our accounts so that we can plan savings and expenditure then can also group our expenditure so that we can see the sort of goods and services we are buying. (This only works if the bank has access to the breakdown of the products we have paid for in a single transaction or it can determine from the name of the organisation the nature of the product. An amazon invoice for example could be for almost anything.) This can be a very useful budgeting tool to help with an individual's financial situation.
Information can be stored and if searchable used again. Other people's experiences of holiday locations, disasters when cooking or advice on why your car may not be working are all available through research and can be extremely useful.
Of course it is possible for people to write biased unvalidated reviews and in this case be caught out.
The benefit of storing information in a searchable format is that parameters such as location can be applied. This could be as simple as searching online for "Chiropractors near here" which would bring up a list of local practitioners. This does not mean that chiropractors do not exist anywhere else but has merely limited the search so that you are only shown those within a suitable distance of your current (or specified) location.
Certain news apps make use of location services so that only local news or news that is relevant to an interest that you have already indicated will be shown.
Benefits and limitations.
Most information is presented for a clear and beneficial purpose. This benefit may only be felt when the information is accessed and used. For example, a student is given an idea of their likely grades to show them in which subjects they are making good progress. If the student uses this information to choose subjects to continue studying, this is a benefit. However, information can also have its limitations. (Knowing limitations is important.)
The list of raw grades may hide the amount of effort that has gone into improving one area, even if that is not reflected by showing a high grade.
3.3 Categories of information used by organisations
Knowledge management and creation
As organisations grow, they need to employ staff to carry out specific tasks which includes access to and use of information. Knowledge management is the process of bringing together all of the information held by an organisation to gain a better insight. For example, one branch of the organisation may be based in a key market and hold specific information that could be used by other branches. If this information is not shared, mistakes could be made or opportunities missed. By managing the information so that it is available to all it is hoped that such mistakes may be avoided and opportunities exploited.
Management information systems (MIS)
A management information system is designed to provide key information needed to aid the management process in making strategic decisions. These systems therefore present an overview of information rather than every detail. The clarity that can be achieved by presenting key information or information that has been gathered by analysing many sources leads to decisions that are based on the "big picture" rather than focusing on small items of information.
An example would be the level of sickness over the previous 30 days that might be held in the industrial personnel record of each member of staff. The nature of the illness, or the names of each individual involved may become important at some stage but an initial decision about the need to use agency staff for example can be based on the overall figures.
Marketing promotion and sales
Organisations use information as part of the process of selling. For example sales figures may identify an increase in sales of a product in a specific region. This could be exploited via the use of targeted marketing, so that the sales in this region could grow even further. Information gathered from customer loyalty cards can provide information about purchasing patterns of key groups, such as those aged under 26. The use of these customer loyalty cards can be also linked to shops in which they were used and organisations can also analyse by geographical area. Such information is clearly valuable in planning marketing campaigns for example.
Financial analysis and modelling
Sales can be measured by units sold or by the revenue raised. Measurements based on the value of the sales is termed financial analysis and can be used to show the information such as the top selling brands or periods during the year when sales are high. This information can be used to create models of expecte3d customer behaviour. For example, if sales figures for a region show that 10 million tins of beans were sold, if the population of the region grew by 25% modelling would suggest that the sales of beans would grow by 25% as well. However, if other factors were important, such as the people buy fewer beans and switch to other products as income grows, this too can be included in the model.
Contact management (CRM)
This is the management of all contact between a business and other people. As an example software could be used to hold all the bookings for a children's party entertainer. The information held would be the actual date and time of the booking, as well as other information such as the name of the client and their contact details.
Information is researched so that a decision may be made; sales figures are gathered so that the future plans may be generated and contacts are managed so that the correct equipment is available for a specific event. Decision making is therefore the fundamental rationale for information use. These decisions could range from whether or not to turn the sprinklers on to water the grass at the Head Office to whether or not to start selling in Bulgaria. Each decision will be based on separate sets of information.
Internal and external communication
In some cases, the information presented is the same. So, for example, Christmas opening hours could be shared with colleagues internally and with customers. The former so that holiday working can be planned and the latter so that shopping arrangements can be made. However other information such as the location of a secret testing facility may only be intended for internal communication. Information on the launch of a new product may be intended for customers.
Big data is large volumes of data - both structured and unstructured - that inundates a business on a day-to-day basis. Big data can be analysed for insights that lead to better decisions and strategic business moves.
Macy's Inc. and real-time pricing. The retailer adjusts pricing in near-real time for 73 million (!) items, based on demand and inventory, using technology from SAS Institute.
There are many examples of big data being used to predict consumer habits in near-real time. Some police departments are using software originally designed to predict earthquakes to predict to within 500 feet where crimes will be committed, reducing violent crime by 21%. IBM refers to 4 different types of big data.
There are four types of big data BI (Business Information) that really aid business:
- Prescriptive – This type of analysis reveals what actions should be taken. This is the most valuable kind of analysis and usually results in rules and recommendations for next steps.
- Predictive – An analysis of likely scenarios of what might happen. The deliverables are usually a predictive forecast.
- Diagnostic – A look at past performance to determine what happened and why. The result of the analysis is often an analytic dashboard.
- Descriptive – What is happening now based on incoming data. To mine the analytics, you typically use a real-time dashboard and/or email reports.
"You can’t manage what you don’t measure.”
There’s much wisdom in that saying, which has been attributed to both W. Edwards Deming and Peter Drucker, and it explains why the recent explosion of digital data is so important. Simply put, because of big data, managers can measure, and hence know, radically more about their businesses, and directly translate that knowledge into improved decision making and performance.
Simple systems with elegant solutions using massive data are now saving lives in rural Kenya.
Benefits and limitations
Effective management and use of information can be key to the success of a business. Contact management can ensure that an organisation keeps its appointments and provides the service that has been booked. Sales data can be used to plan future campaigns and to identify specific markets into which the organisation should move, while a well organised MIS can present management with clear and concise information allowing decisions to be made based on analysis of all the information available.
The limitations of these information systems come from the choice of information that is taken into account when they are created, the quality of the analysis that is applied to the data and the extent to which the information is presented at the time it is required. If either of the first two factors are not met then the information presented will not be correct, while if the information is not available when it is needed, the decisions will be based partly or wholly on guesswork.
3.4 Stages in data analysis
See also Unit 7 (LO1) (text page 197)
There is little conformity in the definition of the stages of data analisis.
Keeping Up with the Quants: Your Guide to Understanding and Using Analytics (Harvard Business Review Press)
OCR suggests an 8 step process:
- 1. Identify the need
- 2. Define scope
- 3. Identify potential sources
- 4. Source and select information
- 5 Select most appropriate tools
- 6. Process and analyse data
- 7. Record and store information
- 8. Share results
Others (Big Sky for example) suggest a 5 step process:
- Step 1: Define Your Questions
- Step 2: Set Clear Measurement Priorities
- Step 3: Collect Data
- Step 4: Analyze Data
- Step 5: Interpret Results
1. Identify the need
This is where the objectives of any data analysis program will be set. By the end of this stage, it should be clear what is hoped to be learnt from the project. This would include all the information that is required from the completed project.
2. Define Scope
This stage defines the restrictions on the project. For example, the overall budget may be set or the time by which the information must be available will be identified.
3. Identify Potential Sources
The planners of a project should be able to identify a wide range of sources and ensure that the information gathered is suitable, provides enough information to cover the objectives. This source information should be unbiased or the degree of bias should be noted in the outcomes of the project.
4. Source and select information
This is the stage where the information is gathered and the best is selected The gathering process uses existing information for example sales figures or population growth projections. The selection process is intended to exclude any information that may not be suitable. For example an interviewer's poor intercessional skills could have a negative effect on the answers given by some interviewees. (The video below demonstrates how the emphasis, question selection and construction can lead to provide different results from the same subjects.)
This information would skew the conclusions based on that specific data set. In such a case it would be better if this information were to be ignored.
5 Select most appropriate tools
See also Unit 7 (LO1.2) (text page 197)
As has been shown information may be presented in many different ways. Charts and graphs present information visually, so that patterns can be discerned. Regression analysis considers how changing only one of many different variables affects an outcome. For example when the possible impact that population growth can have on the sales it has been mentioned that a change in income levels could have a similar effect. The correlation that might be apparent between two variables (population growth and baked bean sales) might have a different explanation.
Regression analysis would try to model the impact of a change in population while holding other possible factors as they were before. This information is generally presented graphically.
An example of regression analysis could be to measure the impact of an increase in price on the sales of a product while at the same time holding all the other variables that could impact on sales such as advertising, customer income and the price of competitors products constant. This results in a clear relationship between the one factor that has changes (product price) and a measurable outcome such as sales figures.
Trend analysis can be presented in many ways but it attempts to present findings over time so that behaviour patterns over a period of time rather than at one precise moment can be identified.
6. Process and analyse data
This is the stage at which the data has been collected is entered into the software and analysed. For example, data could be entered into a spreadsheet and a graph produced to show the information visually.
7. Record and store information
This is the stage at which any report into the findings is written. This includes all of the results that have been processed.
8. Share results
The final stage in the process is when the results are published so that stakeholders may inspect them, This may be in the form of a written report or could be the pages of a website for example.
3.5 Data analysis tools
See also Unit 7 (LO1.2) (text page 197)
A well-structured database uses separate data tables for different types of information. (Its a little more complicated than that but this will suffice for the moment.) For example a database of patients would have one table that just held information about patients themselves (name and address and so forth) and a separate table about Doctors (Their name and department for example) and a third table about appointments (dates and times and which patient is seeing which doctor). A data table can show patterns in the information . For example an appointment query can show the appoint mens for a specific doctor for a certain day or all of the visits to a department in a number of days or all of the appointments for a particular reason over a period.
A number of patterns can be observed in the data. Firstly most of the patients will have booked an appointment in advance (if it is an out-patient clinic then all appointments will have been booked in advance). Secondly, seasonal patterns become obvious with increases in appointments for flu and falls in the winter for example.
Visualisation of data
This is a tool used to help people understand the significance of the data by putting it in a visual context. Patterns trends and correlations are much easier to recognise when data visualisation is employed.
BOOKER PRIZE INFOGRAPHIC from Delayed Gratification, the Slow Journalism magazine.
Click here for zoomable version. (I have includedthis just because I can.)
Trend pattern identification
This is similar to data visualisation in that a graph is used to analyse sales over a the same period over the last five years for example.
An important part of data management is making sure that the data that is held is relevant and up-to-date. Data cleaning is the process of removing or improving out-of-date data. For example, if you deliver milk and someone has not ordered from you for the past two years, it is highly likely that they will not order from you in the future so you could safely remove their details from the database. (Actually the data would be archived so that it can be returned if that customer who had decided to try a different dairy returned as a customer.)
Similarly it is good practice to perform periodic checks are made to ensure that the correct address is held for each customer. It might be possible for the same customer to be recorded with two different addresses (many reasons are possible) so contacting the customer via both addressees should identify which one to delete (archive - after all it is an address to which the dairy has delivered).
Geographic information system/location mapping
The ability to track the geographical location of staff or items (or children) that are being shipped (staff shipped?) around the world can be a real benefit for organisations. Products can be tracked so that delivery times can be confirmed with customers (to make sure that you are not in when the parcel is delivered) or items in a warehouse can be found. Customers can track a courier delivery in real time and so more accurately plan their day.
3.6 Information system structure
Open and closed systems, characteristics, benefits and limitations
An open system can interact with other systems to exchange information even if they are on different platforms. A closed system cannot. One of the disadvantages of having a open system is that it is a wonderful playground for hackers.
Open systems are notoriously difficult to create as there must be a common communication system between all the different platforms and systems that need to exchange information. Systems can exchange data quite simply but if the data cannot be interpreted the way the sender's system intended then the receiving system will only receive garbage that it cannot understand or interpret.
Two systems typify the "open" and "Closed" approach to system integration. The Taurus system was to be all things to all systems and despite massively overrunning both in terms of cost and time was cancelled before almost any code was written. the CHIEF system (Customs Handling of Import and Export Freight) was written as and almost entirely closed system with very strictly regulated access points so that other users had to configure their system to interface with CHIEF and not vice versa.
- 1. Describe the difference between data and information
- 2. Identify one benefit of each of the following uses of information to an organisation that sells fruit: a) planning what fruit will be sold on different days b) education of staff about different types of fruit and c) research new varieties of fruit.
- 3. Identify the information that would be required by an organisation wishing to model potential sales growth rates for the next 12 months.
- 4. Describe how creating a future sales growth model benefits the organisation.
- 5. Explain the term "Regression analysis" and describe how it can be used as an analytical tool.
- 6, Produce a table describing the benefits and limitations of open and closed systems.