Delivery in day(s): 4
MIS781 Business Intelligence Assignment Solution
Mobile business intelligence has now become an integrated part of the organisational framework worldwide and many organisations are using the mobile business intelligence for accessing the business related information such as KPIs and business metrics on the digital screen of the mobiles. Mobile applications are using mobile business intelligence to fetch and analyse the back end and displaying the relevant data on the dashboards. Mobile business intelligence is a support system which is based upon the facts and logics and helps in the decision making process. The actual implementation of the mobile business intelligence was started by Apple when it launched iPhone equipped with BI in 2007. iPhone showed the way of accessing the business intelligence on the mobile device and since then many organisations have been following the BI architecture of iPhone and developing mobile applications which are based upon logical and factual access of the business intelligence. This paper analyses the concepts of mobile business intelligence and the Critical Success Factors of Mobile Business Intelligence with respect to the today’s application of business intelligence in the mobile devices.
Mobile access to Business Intelligence
There are 2 ways in which business intelligence is being accessed on the mobile devices:
- Browsers on the mobile devices are used to access the applications from web
- Native applications are developed to access the BI. iOS and Android are the examples of native applications known as operating systems which are used to access the BI
The main benefit of Mobile Business Intelligence is that it allows the user to access the criticalbusiness information in real time with a minimum response time (Atre, 2003). It helps remote workers to fetch the important information on a secured channel and thus helping the organisations in improving the efficiency. Till 2010, Mobile Business Intelligence was not in much use and it was seen only as a medium of viewing the information in different formats on the mobile devices. Mobile Business Intelligence was used only to see the already processed data and Knowledge Performance Indicators. Although, some users went one step ahead and increased the use of Mobile Business Intelligence to set the regular alerts about what was happening at the back end, yet its functionalities were not much explored and utilised (Sammon and Finnegan, 2000).
Key Components of Mobile BI and Architecture
The architecture of a generic Mobile Business Intelligence App is shown on the next page. The first layer in a Mobile Intelligence Application is the repository layer. This layer contains the data which would be accessed by the Mobile Business Intelligence Application along with the user credentials such as username and password. When a user access a Mobile Business Intelligence Application, the authentication is managed by the web services and the information log is maintained.
The next layer in Mobile Business Intelligence architecture is Business Logic Layer (BLL) which is responsible for the calculations and other business related logics as instructed by the client (front end of the application). The request from the client is invoked in the form of web services which generates further request to the database in the form of a query. The security mechanism is also available at this layer which validates the authentication before delivering any data to user. The URL is returned from this layer to the front end in the form of web service. A web server which is also known as application server exists in the middle tyre which is responsible for the connection between the different layers.
Figure 1: Generic Mobile Business Intelligence Architecture
Query execution is the most important process in any Mobile Business Intelligence Application. Once the Mobile Business Intelligence Application is loaded, the front end is displayed to the user. On the action from user, the Java script API is invoked which is responsible for the SQL statement execution at the database and a database object is created. The business logic is performed and the result is sent to the user in the form of SQL result object (Ballou and Tayi, 1999).
Benefit of the Mobile Business Intelligence
Since its inception, Mobile Business Intelligence has brought revolution in the access of data for remote users. The first thing which is related to the technical aspect is that Mobile Business Intelligence has solved the problem of limited bandwidth. Unlimited data could be accessed through Mobile Business Intelligence applications (Srivastava and Chen, 1999). It has also brought synchronisation among the different technologies and protocols. The most important benefit of Mobile Business Intelligence is that it has enabled the professionals in having the real time data on their devices which has made the process of businessdecision making fast and efficient. Instead of the computers, professionals can now access the detailed information on their mobiles and also in the rich format. Not only the simple and smaller applications but also the large and complex applications are now available on the mobile devices.
Three main benefits of the Mobile Business Intelligence are:
- Exception and Alerts
Mobile Business Intelligence applications are now developed with specific alerts and exception facilities. Users can receive important alerts on their devices because of the Mobile Business Intelligence (Yeoh and Koronios, 2010). Inventory alerts to a salesman is an excellent example of Mobile Business Intelligence. A salesman needs to have the updated inventory condition when it meets with clients. There are some situations when the condition of the inventory is changed since the departure of the salesman from the site. In this case, he can receive the alert of the changes in the inventory periodically so that he can inform the clients accordingly. It helps a salesman in avoiding an embarrassing situation cause by any problem in the supply of the products. If there is a delay in the delivery of a product or the unavailability of the product in the inventory is known to the salesman in real time, he can handle the situation by taking up some proactive actions (Carr, 2003).
- Push reporting
Mobile Business Intelligence has started the trend of push reporting. Some useful information such as Key Performance Indicators is sent to the executives as regular updates using the Mobile Business Intelligence. An example of push reporting is the delivery of the weeklyfinancial statement to the finance executive in an organisation.
- Pull Reporting
Any data which is available on the servers of an organisation could be accessed by its executives by using Mobile Business Intelligence applications. They can also have the customised information on their mobile devices which filters the information on the basis of the parameters entered by the executive on the front end of the Mobile Business Intelligence application. These parameters are used by the business logic layer to process the information from the database and sent to the user in the desired format.
Sometimes, many executives face problems in deciding the kind of data they want and what parameters they need to enter in the application. To handle this problem, Mobile Business Intelligence applications are now providing many sets of KPIs and show them to the user in the form of various reports, graphs and charts (Chen et al, 2000).
Nowadays, not only the information technology organisations but other organisations in different industries have been using MBI in their day to day activities. Tesco has adopted the Mobile Business Intelligence as a medium to keep its delivery managers informed about the daily sales. Tesco is also using the MBI for helping its supply chain management process where line managers receive regular updates on the production. This has helped Tesco in running its business effectively and efficiently. Suppliers of Tesco also receive automated alerts on their mobile dashboards about the inventory and the required materials are delivered to Tesco automatically by the suppliers on the basis of the alerts it
receive without any formal request for the delivery of material from Tesco.
Figure 2: Mobile Dashboard Components
Critical Success Factors (CSF) of Mobile Business Intelligence
Critical Success Factors are the business processes or some specific processes of a business organisation which needs to be implemented and executed perfectly on order for that organisation to be successful in the industry.
Figure 3: Critical Success Factor Framework
The critical success factors ensure competitive advantage for an organisation in the market if the results in these areas are as per the expectations. Similarly, if the outcomes in these areas are not up to the desired level, the whole organisation will be affected in a negative manner. Hence, it is essential that these areas get proper attention from the organisation and should be labelled as the critical areas.
There are 3 main dimensions of the Critical Success Factor framework in Mobile Business Intelligence as shown in figure 2. These dimensions are explained below:
Commitment, management support and sponsorship
Support of the management is crucial for the implementation of the mobile business intelligence. Not only the funds from the management but also the supply of skilled resources essential for mobile business intelligence (Chenoweth et al, 2006). According to the experts, a mobile business intelligence framework development in an organisation is an IT project which should be treated in the same manner as another IT projects. It is not necessary that an organisation needs to be in the IT field for the implementation of the mobile business intelligence. It could outsource the project to other organisation. But the main thing is the support it gets from the business executives in the organisation which decides the success of the framework (Watson and Haley, 1998).
Ultimately, the mobile business intelligence would support the business decision making for the organisation management, so it should be treated in a respected manner by the management.
Clear vision and well-established case
The critical success factor for mobile business intelligence is that it should be aligned with the organisational goals and strategy. If the mobile business intelligence does not meet the strategic goals of the organisation, it would also not meet the needs of the people who would be using it. Hence, it would lead to the failure of the system. Mobile business intelligence is a business eccentric process and should be supported by the business and driven by the business (Farley, 1998).
This leads to another fact – the understanding of the mobile business intelligence by the leadership of the company. Unless the leadership understands the pros and cons of the mobile business intelligence, they would not be able to support it. Hence, knowledge management at the organisational level is mandatory for mobile business intelligence.
Business centric championship and balanced team composition
A champion from the business side in the organisation is required with excellent business knowledge for the success of mobile business intelligence. Mobile business intelligence is a rapidly changing concept which is evolving with time. Hence, a business champion, who has the foresight of predicting the future organisational changes, is needed to make the proactive decisions. Improvisation is necessary when it comes to mobile business intelligence (Wixom and Watson, 2001). A team under the leadership of the business champion would be able to analyse the needs of the organisation and then turn those needs into the mobile business intelligence architecture. The design of the dashboard of a mobile business intelligence application is the first thing which is noticed by the executives and it should have the right design to support the requirement of the user. Only a team with the knowledge of the business and practical approach could design such a system.
Business driven and iterative development approach
When it comes to design a mobile business intelligence application, it is essential that the targets set are realistic, achievable and have a clearly defined scope. A clear scope makes sure that the system is developed and implemented in time as it sets milestones for the project (Gardner and Wong, 2005).
It would be a good idea to design the prototype of the mobile business intelligence application and then use the iterative approach to develop the application. Incremental delivery of the mobile business intelligence application would help in the timely delivery of the application.
User oriented change management
Users should always be included in the mobile business intelligence system. The better involvements of the users help the development team in understanding the exact needs of the users and embed them in the application. For example, a salesman would have a better idea of the data customers ask for in the meetings and the mobile business intelligence application should be able to get him that data in a format that he could show and explain to the customers.
Scalable and flexible technical framework
Business needs are dynamic and to handle these business needs, a mobile business intelligence application should be scalable and flexible so that it could accommodate the technological changes when it comes to handling the dynamic business needs. A mobile business intelligence application should provide a long term solution to the business problems instead of just handling the issues at present (Joshi & Curtis, 1999). Hence, an objective methodology should be considered while developing the mobile business intelligence applications.
Sustainable data quality and integrity
Mobile business intelligence systems are there to support a user in the decision making process which makes it mandatory that the data in the system is uncompromised. The backend of the mobile business intelligence application, which is a database, should be tested thoroughly before releasing the system in real time. If there is a problem with data quality at backend, it would definitely affect the decision of the user as he is dependent entirely on the reports and charts shown on the mobile device. What is the use of an intelligent mobile application if the result is not intelligent?
Compatibility with the devices and operating systems
Although, the significant use of mobile business intelligence started with iPhone, nowadays, the Android mobiles are also being used for running the apps which provide mobile business intelligence. When a mobile business intelligence application is developed, it is essential that it is compatible with all the smart phones and operating systems such as Android, Windows and iOS. An organisation cannot ask all its executives to use a mobile device which uses a specific operating system. Hence, all the devices and all the operating systems should be kept in mind while developing a mobile business intelligence application.
The critical success factors relevant to mobile business intelligence are summarised in the below table:
Fast implementation, Ability to adjust to business requirements, Useful information, Ease of navigation
Management support, Adequate resources, Change management, Metadata management
Watson and Haley (1997)
Chen et al (2000)
Business driven approach, Management support, Adequate resources including budgetary and skills, Data quality, Flexible enterprise model, Data stewardship, Strategy for
Sammon and Finnegan (2000)
Management support, Enterprise approach, Prototyping data warehouse use, Metadata, Sound implementation methodology, External support (consultants)
Little and Gibson (2003)
Data quality, Technology fit, Management support, Defined business objectives, User involvement, Change management.
Mukherjee and D’Souza (2003)
Technical factors (data quality and data consistency, etc.)
Rudra and Yeo (2000)
Project-related factors (project plan must match with business demands and the scope of project management), Technical factors (DBMS selection, data loading, and efficiency of data access, etc.)
Joshi and Curtis (1999)
Data quality, System quality, Management support, Adequate resources, User participation, Skilled project team.
Wixom and Watson (2001)
Management support, Champion, Architecture (data marts), Organisational Fit/User Acceptance
Chenweth et al (2006)
Management support, Clear vision and business case, Business champion, Balanced team, Iterative development approach, Change management, Suitable technical framework, Data quality
Yeoh and Koronios (2010)
Table 1: Critical Success Factor
Farley (1998) emphasised on the ease of navigation for the effective mobile business intelligence application. It is not necessary that every user of the mobile business intelligence is from a technical background. So the ease of navigation is a critical success factor in mobile business intelligence. When mobile business intelligence was introduced in Apple iPhone in 2007, the navigation of the mobile business intelligence application depended highly on the configuration of the iPhone. The front end of the applications developed for iPhone did not have very user friendly interface which was later corrected.
User Satisfaction is another critical success factor as described by Chen et al (2000). An organisation cannot force its employees to use a mobile business intelligence application unless they are satisfied with the features of the application. The format of the Knowledge Performance Indicators and other alerts need to fulfil the requirements of the executives who use it. As long as, mobile business intelligence satisfies its users, they will use it, but if it makes thing more complex, they might avoid using the mobile business intelligence (Karlsen et al, 2006).
Sammon and Finnegan (2000) focused more on the automated data extraction facilities. Instead of pulling the data using mobile business intelligence, it would be useful to provide push facility. If users get the automated alerts and notifications on their mobile devices time to time, it would be easy for them. But there is a problem in this approach. Not all the users of the same application would need same information. Some information which is critical and necessary for one user might not be of use for another. Hence, mobile business intelligence should be extended further while implementing push facility. The users should be able to set the preferences for the information they want to use. In this manner, a user would only receive the alerts and notification which are useful for him. For example, a sales manager at Tesco needs the daily and weekly sales reports while a manager who handles the production process needs regular updates on the supply chain management.
Joshi and Curtis (1999) stated that data loading and efficiency of the data access are the critical success factors for mobile business intelligence. When a user opens a mobile business intelligence application, the loading time of the dashboard becomes very important. If the loading of data and data access after the request takes unusual more time, it would discourage them from using the application. Real time data processing with fast speed is essential for the decision making process (Little and Gibson, 2003).
Wixom and Watson (2001) said that the user participation in the mobile business intelligence is the critical success factor for MIB. It is the end user who ultimately uses the mobile business intelligence for business decision making and he is the ideal candidate to let the developers know about the features he expects in the MIB application.
Limitations of Mobile Business Intelligence
Although, the mobile business intelligence has evolved into a technology which has changed the traditional way of decision making process for the remote people, there are some disadvantages also which are mainly concerned with the mobile devices (Mukherjee and D’Souza, 2003).
Poor resolution of the mobiles makes it difficult to view the reports and KPIs. Same report on the laptop or tablet displays better because of the high resolution of the devices. Although, the latest mobiles have higher resolution than the older devices, it still cannot match the system resolution. Another issue with mobile business intelligence is the small screen of the mobiles. Lower resolution with smaller size screen constitutes a bigger problem in the practical use of mobile business intelligence. Next problem with mobile business intelligence is the low storage available in the mobiles. However some of the latest smart phones have 32 GB and 64 GB storage, but mostly come with 16 GB or less and that is also expandable memory. Original internal memory in normal mobiles is 8 GB which could be expanded to 16 GB. In this case, users might not be able to keep records of the reports and charts they download using mobile business intelligence. The processing power of the mobiles is also slower than the laptops which make data loading a time consuming process and increases the time of decision making process (Poon and Wagner, 2001). Although, the use of in-memory database and increase in the RAM of the next generation mobiles has resolved the issue to some extent, it still cannot match the speed of the laptops.
Security is another concern for the users of mobile business intelligence. Because of the vulnerability of the wireless network on mobiles, the data needs to be encrypted which adds extra load on the application.
The discussion on mobile business intelligence suggests that there are certain critical success factors which are essential for the performance of the MBI applications. Different dimensions of the mobile business intelligence are discussed in the paper and the effect of every factor on mobile business intelligence was described. Organisational dimension is of more important when it comes to mobile business intelligence as they form the basis of the mobile business intelligence. The alignment of the organisational goals with critical success factor is of utmost important.
Mobile Business Intelligence has helped the organisations in having a sustainable competitive advantage in the market. If 2 organisations have the same resources, the use of mobile business intelligence could make lots of difference in the performance of the organisations.
Mobile business intelligence is highly dependent on themobile devices. The configuration of the device and the operating system of the device affect the mobile business intelligence a lot. But there are certain critical success factors as explained in the paper which determines the success of the mobile business intelligence in an organisation. If an organisation keeps these factors in mind while implementing the mobile business intelligence, it could make all the difference. This paper covers the basic of the mobile business intelligence and provides an overview of the CSF in the area. Further researches on the application of the critical success factors in the real world are required. Every critical success factor and its effect on the mobile business intelligence need to be analysed in detail.
Atre, S. (2003). “The Top 10 Critical Challenges For Business Intelligence Success”, C. C. Publishing: 1-8. located at http://www.computerworld.com/computerworld/records/images/pdf/BusIntellWPonline.pdf, accessed June 2007
Ballou, D.P. and Tayi, G.K. (1999), "Enhancing data quality in data warehouse environments”, Communications of the ACM, 42(1), 73-78.
Carr, N. (2003), “IT Doesn’t matter”, Harvard Business Review, May, 5-12.
Chen, L. D., Soliman, K. S., Mao, e. and Frolick, M. N., (2000), “Measuring user satisfaction with data warehouses: an exploratory study”, Information & Management,37(3): 103.
Chenoweth, T., Corral, K. and Demirkan H., (2006), “Seven key interventions for data warehouse success”, Communications of the ACM, 49(1), 114-119.
Farley, J., (1998), “Keeping The Data Warehouse Off The Rocks”, Measuring Business Excellence2(4), 14-15
Gardner, C. T., and Wong, M., (2005), “Intellectual Capital Disclosure: New Zealand Evidence”, proceedings of the Accounting and Finance Association of Australia and New Zealand Conference, Melbourne
Joshi, K. & Curtis, M. (1999). Issues in building a successful data warehouse. Information Strategy, 15(2), 28-35.
Karlsen, J. T., Andersen, J., Birkely, L. S., Odegard, E., (2006), “An empirical study of critical success factors in IT projects”, International Journal of Management and Enterprise Development, 3(4), 297 - 311
Little, R. and Gibson, M., (2003), “Perceived Influences on Implementing Data Warehousing”, IEEE Transactions On Software Engineering29(4), 290-296
Mukherjee, D., and D’Souza D., (2003), “Think phased implementation for successful data warehousing”. Information Systems Management, 20(2), 82-90.
Poon, P., and Wagner, C., (2001), “Critical success factors revisited: success and failure cases of information systems for senior executives” Decision Support Systems30(1), 393–418,
Rudra, A., and Yeo, E., (2000), “Issues in User Perceptions of Data Quality and Satisfaction in using a Data Warehouse - An Australian Experience”, proceedings 33rd Annual Hawaii International Conference on System Sciences (HICSS), Hawaii
Sammon, D. and Finnegan, P., (2000), “The ten commandments of data warehousing”, ACM SIGMIS Database,31(4): 82-91.
Srivastava, J., and Chen P. Y., (1999), “Warehouse Creation - A Potential Roadblock to Data Warehousing”, IEEE Transactions On Knowledge And Data Engineering, 11(1), 188-127
Yeoh, W. and Koronios, A., (2010), “Critical Success Factors For Business Intelligence Systems”, Journal of Computer Information Systems, Spring, 23-132
Watson, H. and Haley, B., (1998), “Managerial Considerations”, Communications of the ACM,41(9): 32-37.
Wixom, B. and Watson, H., (2001), “An Empirical Investigation Of The Factors Affecting Data Warehousing Success”, MIS Quarterly25(1), 17-41