need help!

Running Head: BUSINESS ANALYTICS IMPLEMENTATION PLAN 1

BUSINESS ANALYTICS IMPLEMENTATION PLAN 13

BUSINESS ANALYTICS IMPLEMENTATION PLAN PART 1

Matthew Roewer

Argosy University

Data Driven Decision Making MGT334

09/15/2015

TABLE OF CONTENTS

CHAPTERS

CHAPTER 1 – Introduction ........................................................................................... 3

CHAPTER 2 –Description of the business...................................................................... 3-4

CHAPTER 3 – Benefits of business analytics.................................................................... 4-6

CHAPTER 4 –Disadvantages of business analytics ....................................................... 6

CHAPTER 5 –Challenges of business analytics ...............................................................7-8

CHAPTER 6- Business analytic techniques...................................................................8-9

CHAPTER 7- Implementation of business analytics plan....................................................9-10

CHAPTER 8- Backup proposal.........................................................................................10-11

CHAPTER 9- Conclusion.......................................................................................................11

CHAPTER 10 - References list..............................................................................................12

BUSINESS ANALYTICS IMPLEMENTATION PLAN PART 1

INTRODUCTION

Many businesses enterprises are eager to implement business analytics to help them cut the cost and raise revenues. These companies might face an unchartered territory in the area of business analytics and need assistance in how to solve implementation come ups. Among those issues are a mapping business aims to analytics, resources, budget, data understanding, and planning. The purpose of this plan is to assist companies in dealing with those issues(In Wang, 2007).

For the purposes of this policy, we will equate analytics with the ability to predict the probability of an occurrence or an event in the future. Companies are using analytics in many ways to predict the likelihood of

· Transactions that have much potential to be fraudulent in market surveillance institutional trading and health care claims to process.

· Clients that should be aimed to buy different software products that are together.

· The failure of machine parts within a particular product at the customer site and during the manufacturing process.

Description of the business

Business analytics is skills, techniques practices for continuous iterative exploration and investigation of past performance of the enterprise to gain and drive business planning. It is therefore well known that business analytics makes extensive use of statistics analysis of explanatory and predictive modeling and fact-based management to drive decision making. Occasionally, analytics may be used as an input for human decisions or may drive fully automated decisions. An example of a business that can apply the use of analytics is the banks. Banks can use data analysis or analytics the way it is known in business settings to differentiate among customers. All these get a base on the credit risk, usage, and other characteristics and then to match clients characteristics with appropriate product offerings. As a result, it will prove to be beneficial to the bank due to the easiness in dealing with the customers.

Benefits of business analytics.

Big data analytics brings immense economic value to businesses across industries. For instance, banks use business analytics to detect fraud and prevent losses. Retailers may use it to identify destinations for opening new stores, and pharmaceutical companies dealing with drugs, use it to cut the time-to-market of new medicines(Ibm, 2007) .

Business analytics provides insights into fundamental questions about the organization such as ‘what is taking place’, ‘what will be happening if trends continue’ and ‘ how to improve business outcomes’. Specifically, it can offer the following substantial benefits for companies of every shape and size.

Improve supply of chain management

In a changing business environment, enterprises that have a ‘reactive approach’ to provide control will fall woefully short on their product distribution and price competitiveness. Data analytics can be used to predict demand, reduce production cycles, reduce inventory, and reduce warehouse costs. Analytics also can be used to spot supply inefficiencies as they occur, allowing supply heads to address the capabilities before they affect the customer. A Greater flow of information across management, engineers, and operators is conducive to identifying opportunities for greater production efficiencies.

Create responsive marketing strategies

Analytics marketing is at the heart of a reactive marketing strategy. Marketing analytics can help your business determine the ideal product mix and assess the effectiveness of ongoing business promotions. To add to, identify new product or service opportunities, optimize the use of sales force, and maximize returns from media spends.

Customize customer lifecycle management

Customers retanation is crucial for improving profitability. It means improving the customer experience, meeting lifecycle of customers needs, and proactively identifying profitable customers that shift to competition. Business analytics will improve the service experience across your call center and in-store locations. It allows one to create highly specific customer segments to tailor services and products to meet specific requirements, as well as develop effective retention strategies for clients at risk of flight.

Lower enterprise risks

Analytics tools can get used for realizing anomalies and fraud in real-time, across operations, sales, and financial transaction processing. In the financial services and insurance sector, business analytics is vital to reducing the risk of credit default, and ensuring regulatory compliance.

Improve online marketing efforts

Web analytics can be used to gauge the effectiveness of your business website, online ads and social media strategy. It gives you insights such as who are the visitors to your site, what information are they looking for, and how you can you induce them to take the desired action. Using these insights, you can tailor digital marketing strategies as per customer interests, demographics, and preferred online channel.

Disadvantages of business analytics.

• Price-fixing because of an accurate and reliable quality of information. At times, this proves to be disadvantageous to Consumers. It is so because the enterprise will need to gain from the expenses that they incur while incorporating the business analytics plan. As a result, they will fix a price that will enable them to gain at least some profits in return and through this price fixations customers will end up feeling the pressure of addition.

• Can be time-consuming in terms of Collection and Interpretation of Data. Through the use of a given business analytics method, it will require data to be collected and the same data to get an interpretation. As a result, a lot of duration will be incurred while performing these tasks. Hence, this makes business analytics plan to consume a lot of time.

• Data Analysis Tools may be expensive. The data that need to get looking at details may prove to be the valuable time. It is so because of the requirements that will get requirement in analyzing the data given in any business enterprise. Its expansiveness will result from costs incurred in an analysis of the data.

The banks, for instance, can be proactive in addressing the challenge of price-fixing for reliable quality information in order not to put more pressure on customers. Banks can at least reduce the interest rate that they impose on any of their client who take the loan. Also, banks can reduce the transaction fees that they charge to their customers. When this is done, the bank will attract more customers hence still maintaining the profitability ratios.

The Challenges of Business analytics.

Strategic Alignment. Most organizations nowadays already have some element of business analytics in place, often in the business intelligence or data warehousing area. Unfortunately, analytics is often viewed by top executives as esoteric research at right and irrelevant fringe experiments at worst. The issue rounds not a lack of appreciation of the usefulness of information but a lack of alignment, availability, and trust.

In addressing this challenge, the organization can review the goals of business that support the strategies main for the company, and for each primary market that underpins the goals.

Agility.

Typically in the organizations, the analysts get organized by business domains. Getting Working with, information-driven companies demonstrate that domain-based organizations are not the most practical approach for analytics. Analysts often work solely and create models in ad-hoc environments based on the extracts of patchwork and sources. The outcomes, while advanced and valid, are not commonly communicated to the business users for whom they would provide the greatest value.

Addressing the Challenge, the organization needs to liberate the organizational, analytical capabilities by pooling analysis into a middle of excellence highly focused on good skills.

Commitment.

Analytics software packages often come as a prefabricated solution and are not particularly difficult to implement; however they can be costly. By their nature, analytical models improve in accuracy over time as the results predicts are compared with actual events hitting the warehouse. But this is a tight endeavor that requires intense dedication to the solution during an extended tuning timeline. Here is where many deployments fail to occur. Business users do not immediately see the promised results and lose interest, and executives lose trust in the solution and deny to rely on what the models tell them.

In addressing this challenge, there need to show commitments by both parties in the organization. Also, there is the need to display a lot of dedication by top management and workers in general.

Information Maturity.

The world's best hammer is nothing without nails, and so it goes for analytical equipment. For business analytics solution to succeed, the "nails" need to be plentiful and not consistently bent or misshapen. Implementations often do not because of the lack or low quality of underlying transactional data. Either data are not available, data sources are too complex, or data are poorly mastered. Even bleeding-edge, sentiment- and context analysis tools require some level of trust in the data, and for the analytical model the rule is consistent: the more trustworthy the data, the more reliable the result.

In addressing this challenge, the organizations needs to perform a maturity assessment on the company's information architecture. Identify data sources based on a mapping of analytical requirements; measure the quality of both operational information and aggregated information in the warehouse. To add to, review the existing integration infrastructure's ability to support new sources and data conduits.

Business analytic techniques.

Some of the company analytics techniques include Customer analytics, social media analytics, and operational analytics. First, customer analytics methods involve, predicting consumer behavior in terms of the relationship with management, pricing, product design, promotion, and direct sales and marketing campaigns. Some benefits it has includes, it enables the organization to develop proper interrelationship with its customers. Also, it makes the clients aware or any development that the body tends to make regarding the operation of its business. Finally, the result of this analytics can be used to design more personalized direct marketing. The disadvantages of this technique are, there is a lot of time taken in making the bond with the consumers and also there is some lack of cooperation by some consumers on many occasions.

Social media technique is one of the best techniques since millions of consumers use social media at any given time. Any new product posed will attract several tweets as forms of comment over the products. Some benefits of this technique are; there is the comprehensive view of the product or service for any given company. Also, it enables the company to get easier feedback regarding their products or services instantly based on the comments. The disadvantages of this technique are that customers must be able to access the social media services to be at a position of viewing any product or service of any given company. Also, there is much cost incurred by both the organizations and the consumers for both parties to access the network services.

Operational techniques are majorly used by many organizations to improve existing operations. At times, it is used to predict lead times of shipments and other constraints in supply chains. The advantages that can be gotten from this techniques includes, it contain some software that can present a graphical view of supply chain, which can depict any constraints in events such as shipments and production delays. Another benefit is that it makes the shifting of the business to be smooth and efficient. On the disadvantages part, operational techniques consume a lot of time in terms of its implementation due to the re-creation of the possible events. Another disadvantage is that gaining of the related software a time proves to be much expensive.

Implementation of business analytics plan.

Implementing business analytics to capitalize on sizeable data requires the engagement of every part of your organization( Isson, 2008). Changes in IT must be matched by the organizational change because you won't get value from what you learn about your company if you are not structured to take advantage of it. That approach should include:

• Plan. Create a detailed plan for the project first. Gather resources and inputs, assemble the team of business and IT skills, and ensure that the sponsorship and communication are in place and adequate.

• Discover. Build an analytic development environment to develop, test and refine an initial set of analytics. Preliminary results allow you to assess the business impact and make recommendations. Early success will ensure that sponsorship and buy-in stay strong across the industry.

• Act. Execute a plan using technology so you can make use of your big data insights.

• Embed. Embed, the analytics capability of the organization. It will include potentially far-reaching changes to processes, people, organization, data, applications, and technology.

Backup proposal

The Strengths, weaknesses, opportunities and threats analysis is an important part of business planning. An adequately prepared SWOT analysis tells entrepreneurs that you have realistically and objectively considered these elements (Gendron, 2009) . It is one of the back up proposal that can be used instead of business analytics.

Banks and other lenders understand that companies will encounter hard times at some given point, and want to get to know how you will deal with these challenges. Remembering that overestimating strengths and opportunities or ignoring potential challenges will undermine someone credibility.

Putting duration and efforts into conducting an intense SWOT analysis can help you:

• Make clear decisions and plans

• Anticipate the problems and make the necessary changes

• Set aside more resources to take advantage of potential opportunities

CONCLUSION

In this article, the transformational power of data, whether big or small is essential. However, the force is not in data alone but also as it is being refined through analysis. Although some analytics has become part of the daily vernacular, we have precisely defined Business Analytics as “the process of knowing of actionable knowledge and the making of new business opportunities from such knowledge.”

To show the applications of analytics to answer many critical plans. Within each scheme, ways of applying analytics were also proposed. The vital lessons people learned in more than a decade of using analytics in businesses were also shared.

The main lesson is to link tightly analytics to business. To do this, you have to create safe and productive interacting staffed by analytics starters who are well-versed in business and analytics, supported by an analytics sandbox as part of the integrated business plan.

References

Gendron, M. S. (2009). Business Analytics Applied: Implementing an Effective Information and Communications Technology Infrastructure

Ibm, R. (2007). Complete analytics of query management facility: Accelerating well-informed decisions. S.l.: Vervante.

In Wang, J. (2007). Encyclopedia of business analytics and optimization.

Isson, J. P., & Harriott, J. (2008). Advanced business analytics: Creating business taste from your data. Hoboken, N.J: John Wiley & Sons.