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Decision Making Techniques
Decision Making Techniques
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Go Globalor No? In my view, the answer is "not yet." To survive, DataClear has to go global in the future but its current decision-making process and rationale are flawed. What DataClear needs to do is to not panic, slow down, and take a clearer look at its situation and the business environment and develop some strategic options that will allow it to go global when the time comes.
They've got some time but not a whole lot of it. As stated in the case, they need to focus.
Despite VisiDat's emergence and its contract with Shell, DataClear still has the data analysis market in the U.S. to itself, as well as a proven product to sell. VisiDat's product was still in beta and had no successful installations, and there is no guarantee that it will perform as well asmuch less outperformDataClear's.
DataClear had also recorded very impressive sales growth in its first two years and, given the projections, were looking at 300 percent average revenue growth thru '02. The case analysis available shows that DataClear has a $600 million annual domestic market for its current product and $1.2 billion when you add in the global market in telecommunications and financial services. With product expansion, there was a potential annual $2.7 billion market ($1.5billion domestic/$1.26 billion abroad) to target in the telecommunications, financial services, chemical, petrochemical, and pharmaceutical industries combined.
The case also suggests that DataClear would not have to substantially modify its core software product in order to accommodate expansion into new markets for its services, although the total cost of expanding both product and infrastructure/staff support was put at $4 million. The cost of immediate global expansion was not explicitly stated but probably somewhere around $2 million just for infrastructure and staff support, before product development (let's call that $2 millionso it's even).
What was clear in the case was the lack of international business experience on the part of DataClear's senior managementa serious shortcoming. Before thinking about going global, DataClear must get smarter about the international scene and get some real expertise on board.
My recommendation is that DataClear first press ahead with consolidating its first-mover advantage in the U.S. telecommunications and financial services markets and expand as planned into chemical, petrochemical, and pharmaceutical data analysis. In all these areas, the companies it deals with or will be marketing to are global players so, in effect, DataClear is already developing a global presence.
Next, I would get a copy of or access to VisiDat's product to see just how good it really is and determine it's shortcomingsthis will aid in refining the ClearCloud product as well as follow-ons.
Data Analytics has significantly grown in less than two years, this quick growth has caused the company to evaluate the IT environment and its ability to support the growth and secure the data of the company. The CEO is expecting the company to grow 60% over the next two years; with the success of the company it has been determined that a change to the current IT environment and infrastructure must occur to better support the employees and the customer base.
In 1994, Jim Donehey was brought in to update Capital One’s IT system. His solution was to replace their aging mainframe computers with an object-based system, but this technology had never been used on such a large scale. In contrast, two-thirds of Capital One’s competitors outsourced their IT functions. Within 5 years the company had the world’s largest Oracle database with 23 terabytes of data – winning them the Gartner Group’s Excellence in Technology Award.
Tableau software is making it easier for businesses to analyze data to better their business strategies and intelligence. This software also allows you to connect to specified information from many different sources and can then analyze the collected data in multiple ways. Tableau software ensures that companies are seeing the same picture across multiple departments and levels.
Big Data is changing the arena for big businesses. Big Data is the technology trend that has made it possible for businesses to better understand their markets. Big Data is the new natural resource, the new “oil.”
Big Data has gained massive importance in IT and Business today. A report recently published state that use of big data by a retailer could increase its operating margin by more than 60 percent and it also states that US health care sector could make more than $300 billion profit with the use of big data. There are many other sectors that could profit largely by proper analysis and usage of big data.
III. Situation Analysis Company Analysis During the 1970's, HD was facing a decline in market share due to increased competition with Japanese companies. By phasing out weak models, becoming more selective, and limiting sales and promotions, HD was able to carve out a niche in the marketplace which it enjoys today. Now again, faced with a period of decline, HD is relying on its newly adopted marketing objectives. First, HD needs to expand its potential customer base to include enthusiasts and non-enthusiasts.
In 1977, Larry Ellison, Bob Miner, and Ed Oates founded System Development Laboratories. After being inspired by a research paper written in 1970 by an IBM researcher titled “A Relational Model of Data for Large Shared Data Banks” they decided to build a new type of database called a relational database system. The original project on the relational database system was for the government (Central Intelligence Agency) and was dubbed ‘Oracle.’ They thought this would be appropriate because the meaning of Oracle is source of wisdom.
Some challenges are business related. Many software suppliers use non-standard software to "lock in” vendors - i.e. make it difficult to migrate their data to a competitor. Business models that are predicated on historical service delivery models, such as face-to-face, fee-for-service consultations often penalize remote service delivery.
Evidently, there are many benefits to working with Big Data analytics and procedures, and as computing capabilities continue to advance these benefits are only projected to increase. Data’s value is now more dependent on its cumulative potential uses than its initial use; however it is unlikely that a single firm will be able to unlock all of the dormant value from a given dataset. Therefore, in order to maximize Big Data’s value firms can license their accumulated data to third parties in exchange for royalties. In doing so, all agents have incentive to maximize the value that can be extracted by means of re-using data.
Byte Products, Inc., headquartered in the midwestern United States, is regarded as one of the largest volume supplier for the production of electronic components used in personal computers. Byte Products, Inc., was a privately owned firm that has now entered to be a publicly traded company. The majority of the stockholders are the initial owners of Byte, when it was still privately owned. The products that Byte produces are primarily found in computers used for business and engineering applications. Byte Products, Inc., has been the leader in this industry for the past six year with consistent yearly revenues of 12% and total sales of approximately $265 million. Byte also has 32% of the market share.
Identify your need of the data recovery- Data recovery is one of the most vital strategy for the survival of your business. All companies have unique data that marks their uniqueness in the market. Therefore, safeguarding data is an important task. Even when the data is lost make sure you’re ready to face such a crisis strongly with proper
Volvo began the challenge of big data in 2006 when they formed a partnership with the Teradata Corporation and began to build their first data warehouse and change their process and IT infrastructure to create and more responsive, scalable and accurate information system.
Prior to the start of the Information Age in the late 20th century, businesses had to collect data from non-automated sources. Businesses then lacked the computing resources necessary to properly analyze the data, and as a result, companies often made business d...
petabytes of junk. Data must be accessible and query-able. When we say that we have