Performance Gap at eBay

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eBay is a multinational online consumer-to-consumer company based in California, USA. It was started in 1995 by Pierre Omidyar (Collier, 2013). The firm has now been transformed into a multi-billion dollar enterprise with operations spread to more than thirty nations. Its core business is composed of an online shopping and auction website; businesses and individuals purchase and sell a wide range of commodities and services globally. The website has grown to incorporate standard shopping, classified advertisement, event ticket exchange, and money transfers among others. eBay is one of the world’s markets and the largest recycling center. The firm deals in merchandise sales and auctions on the internet. The provision of a global market and timely collection of taxes are at the heart of eBay’s business model. eBay neither runs stores nor has warehouses. Its revenues originate from advertising and listing charges, the banking system for internet clients, and PayPal (Collier, 2013).

In 1995 Pierre founded AuctionWeb as part of his site. One of Pierre’s initial sales on the site was a damaged laser point. eBay was run as a hobby until early 1996 when Pierre started charging persons who used his site. Towards the close of 1996, eBay secured a third-party licensing agreement with Electronic Travel Auction. Through the arrangement, the firm obtained the right to transact plane tickets via the Smart market Technology. In January 1997, eBay recorded phenomenal growth; the site registered two million auctions, a shoot from 25000 during the previous year. Towards the close of 1997, AuctionWeb was renamed eBay. On 21^st September 1998, eBay was listed and recorded a tripling effect on its price on the first trading day (Collier, 2013).

The company continued to expand through horizontal and vertical acquisitions. Nevertheless, at the onset of 2006 internet auctions registered a disturbing movement. Owing to the maturation of the internet business, clients grew less willing to wait for days trailing their bids to achieve a good deal. In addition, online buyers were uncomfortable with the toppling of bids at the last minute. With automated software programs, last moment bidding became common. Search engines enabled clients to swiftly locate any commodity at the least price. The convenience of purchasing goods swiftly at a predetermined price gave clients room to save on time. The new development created a performance gap in the company’s operations; the future performance of eBay was at stake.

Data analysis at eBay indicated that the firm’s traditional ploy, online auctions, was getting obsolete. About half of eBay’s transactions were attributable to fixed prices sales while auction sales constituted less than thirty-three percent compared to seventy-five percent in the previous two years. eBay instituted performance gap analysis to bridge the performance gap. The performance gap analysis process involves the definition of a change program’s objectives and system parameters, recognition of problems, symptoms, and the roots of ineffectiveness, identification data collection methods, description of diagnostic models and methods used in online data programs, and application of ordered diagnosis to a firm’s situations. On identifying the areas in need of improvement, the present performance is assessed and the envied levels of output and quality are set (Brown, 2011, p. 117).

Performance gap analysis provides the information needed for a swift response to changes in the business environment. When data analysis was concluded at eBay, the management resolved to alter its strategy by shifting to fixed-price commodities. eBay resolved to concentrate on easing the process of finding goods for consumers (Brown, 2011, p. 120).

Advantages and Disadvantages of Large Quantities of Data

Gathering large quantities of data is essential in maximizing the performance of eBay. Through large quantities of data, selling prices can be optimized, and improved customer satisfaction is achieved. Large volumes of data empower the seller to identify what customers are looking for, what they like, and what they want to buy. Large-scale data accumulation has facilitated the improvement of customer relationship management. Indeed, big data creates customer intimacy and places the customer at the center of the corporate strategy. The availability of large amounts of data eases the acquisition of more customers. Demand signaling becomes easier; this leads to maximization of profit. Through large data, it is easier to targeted customers through adverts (Russ and Preskill, 2001, p. 180)

Large quantities of data are transformative as they take businesses to places. It is easier to perform analysis when you have big data. Big data enhances opportunity creation in businesses. It also enhances service offering as they are offered in real-time. Products renovation and expansion are realized. Through large data old segments can improve including their functions. New businesses models are developed through the availability of large data quantities and especially financial businesses. Big data enhance strategic decision-making. Mass production is realized and this leads to growth and cost reduction opportunities.

The government is not left behind when it comes to benefiting from large data quantities. Big data has enhanced service improvement, taxpayer funds optimization, improved market governance, and better protection through improved weaponry. Fraud detection and prevention are possible through large quantities of data. It is also possible to conduct risk and portfolio analysis when large quantities of data are gathered.

Though the accumulation of large quantities of data provides leverage to identify patterns, trends, correlations, and relationships, it also presents serious challenges to the clients, users, and their systems. The collection of large amounts of data makes it more challenging to analyze and make meaning out of it. Bulk data collection also inhibits the efficiency of the available infrastructure (Russ and Preskill, 2001, p. 181).

The collection of large amounts of data raises privacy and security issues. Many corporations have acquired a lot of confidential and personal information relating to their clients. Unfortunately, most of them have inadequate security resources to safeguard such information (Russ and Preskill, 2001, p. 193). This exposes their clients to infringement of privacy by fraudsters and dishonest employees and misuse of their personal information.

Indeed, the issue of personal privacy has increasingly become a cause of concern particularly with the boom in internet consumption through e-commerce, blogs, social networking, forums among others aspects (Russ and Preskill, 2001, p. 213). Clients are worried that their data is gathered and put into unethical use likely to cause many troubles. Furthermore, businesses or corporations do not last for eternity; they may merge with others, be taken over, or get out of business. In case of such eventualities, the data collected to provide an understanding of customer trends may leak or be sold to other organizations.

Although the accumulation of large amounts of data is essential to understanding consumer behavior, it cannot be useful by itself. Online data analysis needs a specialist to draw objective inferences out of the computerized output. If the specialist inputs an incorrect or inadequate amount of data, the result will be adversely affected (Russ and Preskill, 2001, p. 181).

References

Brown, R. D., (2011). An Experiential Approach to organizational Development.London: Pearson Education, Limited.

Collier, M., (2013). eBay Business All-in-One For Dummies. New Jersey: Hoboken.

Russ, D., and Preskill, H. (2001). Evaluation in Organizations. New York: Basic Books.

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Performance Gap at eBay

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