Review Questions Chapter 12

1. What the different types of decision and how does the decision making process work?

• Distinguish between an unstructured, semi-structured, and structured decision.
  Unstructured decisions occur at higher levels – novel, important and non-routine Semi-structured decisions occur at both lower and higher levels – only part of the problem has a clear-cut answer provided by an accepted procedure Structured decisions occur at lower levels – repetitive and routine.

There are four stages in decision making:

1. Problem discovery – what is the problem?
2. Solution discovery – what are the possible solutions?
3. Choosing solutions – what is the best solution?
4. Solution testing – is the solution working and can we make it work better?

The different levels of decision-making and decision-making constituencies in organizations are:

1. Senior management dealing with unstructured decisions.
2. Middle management dealing semi-structured decisions.
3. Operational management dealing with structured decisions.

Senior management in dealing with unstructured decisions – provide judgment, evaluation, and insight to solve the problem Middle management in dealing with semi-structured decisions – only part of the problem has a clear-cut answer provided by an accepted procedure Operational management in dealing with structured decisions – repetitive and routine, and they involve a definite procedure for handling them.

1. How do information system support the activities of management decision making?

• Compare the description of managerial behavior in the classical and behavioural models

The classical model describe formal management function but does not address exactly what management do when they plan, decide things, and control the work of others.
Behavioral model is actul behavior of management appears to be less systematic, more informal, les relative, more reactive, and less well organized than the classical model would have us believe.

• Identify the specific managerial roles that can be supported by information system
  Mintzberg found that these managerial roles fell into three categories:

1. Information quality
2. Management filters
3. Organization inertial and politics

1. How do business intelligence and business analytics support decision making?

Business intelligence and analytics promise to deliver correct, nearly real-time information to

decision makers, and the analytic tools help them quickly understand the information and take action.

A business intelligence environment consists of data from the business environment, the BI

infrastructure, a BA toolset, managerial users and methods, a BI delivery platform (MIS, DSS, or ESS),

and the user interface. There are six analytic functionalities that BI systems deliver to achieve these

ends: predefined production reports, parameterized reports, dashboards and scorecards, ad hoc queries

and searches, the ability to drill down to detailed views of data, and the ability to model scenarios and

create forecasts.

• Define and describe business intelligence and business analytics
  Business Intelligence
  Business intelligence (BI) is a technology-driven process for analyzing data and presenting actionable information to help corporate executives, business managers and other end users make more informed business decisions. BI encompasses a wide variety of tools, applications and methodologies that enable organizations to collect data from internal systems and external sources, prepare it for analysis, develop and run queries against the data, and create reports, dashboards and data visualizations to make the analytical results available to corporate decision makers as well as operational workers.

  BI data can include historical information, as well as new data gathered from source systems as it is generated, enabling BI analysis to support both strategic and tactical decision-making processes. Initially, BI tools were primarily used by data analysts and other IT professionals who ran analyses and produced reports with query results for business users. Increasingly, however, business executives and workers are using BI software themselves, thanks partly to the development of self-service BI and data discovery tools.

  Business Analytics

  Business analytics (BA) refers to the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods. In contrast, business intelligence traditionally focuses on using a consistent set of metrics to both measure past performance and guide business planning, which is also based on data and statistical methods.(citation needed)

  Business analytics makes extensive use of statistical analysis, including explanatory and predictive modeling, and fact-based management to drive decision making. It is therefore closely related to management science. Analytics may be used as input for human decisions or may drive fully automated decisions. Business intelligence is querying, reporting, onilne analytical processing (OLAP), and “alerts”.

• List and describe the elements of a business intelligence environment
  There are six elements in the business intelligence environment:
  Data from the business environment – data (structured and unstructured) fromvarious sources need to be integrated and organized

  Business intelligence infrastructure – a database system is needed to capture allthe relevant business process data

  Business analytics toolset – tools are needed to analyze data and produce reports,track the progress of the business using key indicators of performance

  Managerial users and methods – managers decide on strategic business goals andhow progress are measured to make full use of BI and BA tools

  Delivery platform (MIS, DSS, ESS) – results from BI and BA are delivered toeveryone in the firm

  User interface – visual techniques such as dashboards and scorecards are used topresent BI and BA results

• List and describe the analytic functionalities provided by BI systems
  The simplest and most ubiquitous (though interestingly often driven the least real value) is reporting. Reporting tells us all about what has already happened. One of the key things about reporting is that it is very static. A key limitation to reports is that, even if they are very parameter driven, they don’t allow users the ability to dig more deeply, aggregate up, etc. thus liming the insights they deliver. Also, by definition, reports are backward looking also limits their value for forward-thinking decisions. Reporting is important (even necessary) but rarely do reports make it obvious what to do next—what to change, what to keep the same, etc. Reports, queries and search tools give us an excellent sense of current or past state and pretty much end there.
  The next function up the complexity and value ladder is Analysis. Because analysis focuses on why things happened, it’s much more valuable for contributing to making good decisions. This is the world of visualization and Online Analytical Processing (OLAP). Graphs and infographics can connect data elements and present them in a way that makes their relationships more obvious; statistical processes can be brought to bear on the data to give us a sense of how reliable those conclusions are; and OLAP tools let us explore these relationships by drilling down to more granularity, up to higher levels of aggregation and across to find relationships that weren’t immediately obvious.
  The critical difference between reporting and analysis is that ability to explore the data and relationships in an efficient way as opposed to being limited to a rigid view of the information. OLAP and visualization tools are key to this competency.
  Monitoring takes us another level higher in complexity. Because it tells us exactly what is happening now, it can provide immense value by allowing us to identify issues, intervene and correct in near real time rather than waiting for a report to tell us how badly we did and the ensuingpost mortemanalysis to tell us why the bad results occurred. Dashboards, scorecards and alerts allow us to make decisions to create good results proactively and avoid bad performance before it accumulates.
  There’s actually a term for this particular form of monitoring. “Operational business intelligence,” sometimes called “real-time business intelligence,” is an approach to data analysis that enables decisions based on the real-time[1] data companies generate and use on a day-to-day basis. This use leverages BI tools and algorithms to improve the day-to-day activities of front-line workers. Examples include tools to help control expenses, utilities, monitor renewals, etc.
  The “holy grail” of BI is predictive analytics (by the way, it’s also where the most snake oil is sold). Predictive analytics process the data to come up with predictions of what might happen in the future. While not yet widespread in multi-family housing, there are some predictive analytics already in the common technology stack. For example, credit scoring applications predict likely bad debt and pricing and revenue management systems predict optimal rents to balance occupancy and yield. Predictive analytics value, when executed well, should be obvious—if we know something about the future, we have even more opportunity to affect that future, or at least to prepare for it as part of our decision making process.

Compare two different management strategies for developing BI and BA capabilities

• One-stop integrated solution
  – Hardware firms sell software that run optimally on their hardware
  – Makes firm dependent on single vendor—switching costs
• Multiple best-of-breed solution
  – Greater flexibility and independence
  – Potential difficulties in integration
  – Must deal with multiple vendors

1. How do different decision-making constituencies in an organization use business intelligence? 

   Operational and middle management are generally charged with monitoring the performance of their firm. Most of the decisions they make are fairly structured. Management information systems (MIS) producing routine production reports are typically used to support this type of decision making. 

   For making unstructured decisions, middle managers and analysts will use decision-support systems (DSS) with powerful analytics and modeling tools, including spreadsheets and pivot tables. Senior executives making unstructured decisions use dashboards and visual interfaces displaying key performance information affecting the overall profitability, success, and strategy of the firm. The balanced scorecard and business performance management are two methodologies used in designing executive support systems (ESS).
   a) Unstructured decisions are those in which the decision maker must provide judgment, evaluation, and insight to solve the problem. Each of these decisions is novel, important, and nonroutine, and there is no well-understood or agreed-on procedure for making them.
   Structured decisions, by contrast, are repetitive and routine, and they involve a definite procedure for handling them so that they do not have to be treated each time as if they were new. Many decisions have elements of both types of decisions and are semistructured, where only part of the problem has a clear-cut answer provided by an accepted procedure. In general, structured decisions are more prevalent at lower organizational levels, whereas unstruc- tured problems are more common at higher levels of the firm.
   b) MIS systems are typically used by middle mangers to support this type of
   decision making, and their primary output is a wet of routine production reports
   based on data extracted and summarized from the firms underlying transaction
   processing systems. The DSS systems rely more heavily on modeling than MIS,
   using mathematical or analytical models to perform what-if or other kinds of
   analysis. The purpose of ESS is to help senior management focus on the really
   important performance information that affects the overall profitability and
   success of the firm. They need to understand what is the really important
   performance information for a specific firm that executives need and they will
   need to develop systems capable of delivering this information to the right
   people.
   What is the role of information systems in helping people working in a group make decisions more efficiently?
   Group decision-support systems (GDSS) help people working together in a group arrive at decisions more efficiently. GDSS feature special conference room facilities where participants contribute their ideas using networked computers and software tools for organizing ideas, gathering information, making and setting priorities, and documenting meeting sessions.
   c) The balanced scorecard framework is thought to be “balanced” because it causes managers to focus on more than just financial performance. In this view, financial performance is past history—the result of past actions—and managers should focus on the things they are able to influence today, such as business process efficiency, customer satisfaction, and employee training. Once a scorecard is developed by consultants and senior executives, the next step is automating a flow of information to executives and other managers for each of the key performance indicators. There are literally hundreds of consulting and software firms that offer these capabilities, which are described below. Once these systems are implemented, they are often referred to as ESS.
   Another closely related popular management methodology is business performance management (BPM). Originally defined by an industry group in 2004 (led by the same companies that sell enterprise and database systems like Oracle, SAP, and IBM), BPM attempts to systematically translate a firm’s strate- gies (e.g., differentiation, low-cost producer, market share growth, and scope of operation) into operational targets. Once the strategies and targets are identified, a set of KPIs are developed that measure progress towards the targets. The firm’s performance is then measured with information drawn from the firm’s enter- prise database systems. BPM uses the same ideas as balanced scorecard but with a stronger strategy flavor (BPM Working Group, 2004).
   Corporate data for contemporary ESS are supplied by the firm’s existing enterprise applications (enterprise resource planning, supply chain manage- ment, and customer relationship management). ESS also provide access to news services, financial market databases, economic information, and whatever other external data senior executives require. ESS also have significant drill- down capabilities if managers need more detailed views of data.
   Well-designed ESS help senior executives monitor organizational performance, track activities of competitors, recognize changing market conditions, and identify problems and opportunities. Employees lower down in the corporate hierarchy also use these systems to monitor and measure business performance in their areas of responsibility. For these and other business intelligence systems to be truly useful, the information must be “actionable”—it must be readily available and also easy to use when making decisions. If users have difficulty identifying critical metrics within the reports they receive, employee productivity and business performance will suffer. The Interactive Session on Management shows how Colgate-Palmolive addressed this problem and helped its managers make more data-driven, actionable decisions.
2. Define a group decision-support system (GDSS) and explain how it differs from a DSS. 

   Operational and middle management are generally charged with monitoring the performance of their firm. Most of the decisions they make are fairly structured. Management information systems (MIS) producing routine production reports are typically used to support this type of decision making. 

   a) The DSS we have just described focus primarily on individual decision making. However, so much work is accomplished in groups within firms that a special category of systems called group decision-support systems (GDSS) has been developed to support group and organizational decision making.
   b) A GDSS is an interactive computer-based system for facilitating the solution of unstructured problems by a set of decision makers working together as a group in the same location or in different locations. Collaboration systems and Web-based tools for videoconferencing and electronic meetings described earlier in this text support some group decision processes, but their focus is primarily on communication. GDSS, however, provide tools and technologies geared explicitly toward group decision making.
   GDSS-guided meetings take place in conference rooms with special hardware and software tools to facilitate group decision making. The hardware includes