Future Business in IT

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Future Business in IT

According to McAfee and Brynjolfsson, the future technology environment section describes what IT determines it needs to do to accommodate business changes. Information Technology plays a crucial role in the future business environment since it paints a picture of how the organization sees the business evolving over the next three, five, or more years. The challenge for managers, within this context, is to learn how to identify that talent, attract it to an enterprise, and make it productive. Scientists are still finding ways and means of improving and adding most value in businesses, as well as measuring the business performance level. As goes the business, so goes the technology. IT can easily understand the impact of future business changes on technology if it documents the effect of business assumption on technology. It is a simple case of cause and effect. In a competitive landscape where challenges keep changing and data never stop flowing, data scientists help decision makers shift from ad hoc analysis to an ongoing conversation with data. Data scientists are the people who understand how to fish out answers to important business questions from today’s tsunami of unstructured information. They identify rich data sources, join them with other, potentially incomplete data sources, and clean the resulting set. If, in future, the business assumption changes, then the technology that is the effect of that cause can easily be identified and changed (75).

Data scientists have the freedom to experiment and explore possibilities within the business. However, most consulting firms are yet to assemble many of the data scientists. Companies often have the data they need to tackle business problems, but managers simply don’t know how the information can be used for key decisions. For example, operations executives might not understand the potential value of the daily or hourly factory and customer-service data at their exposure. That being said, data scientists close relationships with the rest of the business. From time to time again, a point has been made that effective strategies require revision, almost certainly a radical revision of the current way of carrying out the business. Organizations are seen as moving through a number of levels in their use of IT. The most important ties for them, in this context, are to build business relations with executives in charge of products and services rather than with people overseeing business functions. Considering the difficulty of finding and keeping data scientists, one would think that a good strategy would involve hiring them as consultants. Jobs will need to disappear, new jobs will be created, and organizational structures will change, the culture will need to change. The analysis carried out here assumes that such changes once understood can be made (Barton and Court 81).

Organizations that succeed in the enlightened use of technology will increasingly differentiate themselves in the marketplace for talent, raw materials and customers. The challenge of accessing and structuring big data sometimes leaves little time or energy for sophisticated analysis that sometime involves prediction or optimization. For this reason, Information Technology incorporates more resources, human and financial factors, to reproduce applications that are far more complex to identify, describe and begin to impact at many levels in all parts of the organization in a more radical way than in previous activities. Applications that are in line with the organization’s overall business strategy offer the greatest value-added potential (Davenport and Patil 71). Yet if executives make it clear that simple reports are not enough, data scientists will devote more effort to advanced analysis. Increasingly, information technology is bridging social, educational and international distances, and empowering people to perform at their fullest potential.

Companies can impel a more comprehensive look at information sources by being specific about the business problems they want to solve or opportunities they hope to exploit. For example, a banking team that needed to improve the efficiency of its customer-service operations created a 360-degree view by combining information from ATM transactions, online queries, customer complaints, and so on (Davenport and Patil 71). Within this context, it’s a mistake to assume that acquiring the right kind of big data is all that matters. In addition, essential is developing analytics tools that focus on business outcomes and that are relevant and easy to use for everyone from the creative suite to the front lines. This requires transformation of the business organization’s culture and capabilities, not in a rush to action but in a deliberative effort to weave big data into the business.

Conclusion

The future technology environment section describes what IT determines it needs to do to accommodate business changes. For the main purpose of accessing data that will prove useful in boosting future business in IT, data scientists challenge and structure big data sometimes. This leaves little time or energy for sophisticated analysis that sometime involves prediction or optimization. Organizations that succeed in the enlightened use of technology will increasingly differentiate themselves in the marketplace for talent, raw materials and customers. It is, however, a mistake to assume that the acquisition of the right kind of big data is all that matters. Works Cited

Barton, Dominic and Court, David. Making Advanced Analytics Work For You: A Practical Guide to Capitalizing on Big Data. Harvard Business Review, 2012.

Davenport, Thomas and Patil, D. Data Scientist: The Sexiest Job of the 21st Century. Harvard Business Review, 2012.

McAfee, Andrew and Brynjolfsson, Erik. Big Data: The Management Revolution. Harvard Business Review, 2012.