Competing on Analytics
How a company can become and prosper as an analytics competitor
It is essential to appreciate the place of analytics in the business world today. Indeed, as the author reports, the world has become competitive in business circles so that advantages can be derived from exceptional practices such as analytics competition. Analytics competition resonates around the strategic decision making and business operations based comprehensive analysis of data and information gathered by the unit concerned. It is important to evaluate how a company can become and prosper as an analytics competitor.
Becoming an analytics competitor entails an overhaul of the system with the application of entirely different approach to the market. It demands for the company to assume a scientific approach that bases decisions on gathered data, fact and evidence. Analytics competition place the need for comprehensive collection and analysis of data. In that strain, one step towards joining the analytic competitors list involves the adoption of the culture of synthesis and use of data and information. As the author observes, the data does not merely refer to the current or immediate former records. Indeed, it involves the collection of data over a number of years. It also demands that the analysis be comprehensive based on intensive modelling and scientific calculations. This perhaps lays the ground for the second requirement in becoming an analytics competitor. That is the need for modern and advanced technology. It would be essential for the company to rely on technology with advanced features that addresses all the modern demands and incorporates the newly developed technicalities in calculations. It also ensures there is sufficient data to facilitates decision making
In addition to the mentioned two requirements, a company implementing analytics competition would need informed and experienced personnel. The use of analytics is rather complex and requires the brains specialised in that particular field of study with relevant experience. The author rightly observes that analytics needs learned people who can interpret the data and information from the technology in application. Indeed, the author backs the argument by mentioning the decision by Amazon to hire an optimization specialist. He reports that Amazon has been doing well after that.
It is imperative to address the second limb of the question. Exactly how does a company prosper as an analytics competitor? One salient feature that comes out is the need to rely on evidence and hard facts. It does not stop there, prosperity demands that the company culture on decision making be skewed in favour of factual decision making. One cannot help but apply factual analysis and evidence based decision models to succeed. In addition, there is need for companies to do just more than the obvious in analysing data. The company has to apply sophisticated methodologies in analysis of the data gathered. They have to develop elaborate predictive models addressing questions on pricing, target markets, customer relationships, consumer needs, among others. It is imperative to note the role stakeholders play in the success of the analytics competition. The assumption is that all stakeholders would be analysed and concerns so gathered addressed with immediacy. It is on that premise that companies can prosper as analytics competitors.
Sources of strength for analytics competitors
An analytics competitor derives its strength from a litany of diverse advantages. First, the decision making is based on scientifically modelled data and information. The competitor, therefore, makes informed decisions that take into consideration the prevailing circumstances and maximize the opportunities while limiting the threats. The competitor does not merely rely on basic statistics. The analysis is based on in-depth collection and comprehensive data.
Secondly the employee competence levels especially in the optimization and analysis department is on top of its game. This ensures the competitor is well poised to strategize in its advantage and make decisions that are skewed in favour of the competitor. This increases its competitive advantage in the market and positions well for any opportunities in the market. In addition, it can be said that such a competitor is less susceptible to errors and mistakes of judgement.
Going by the authors examples like Boston Red Sox, Amazon and Proctor and Gamble, it is obvious that an analytics competitor derives benefits in the collection of comprehensive data. The data on past performance is an essential strength. This is because the decision making process must be based on data and information. In fact, the author observes that companies adopting analytics must embark on the long and painful process of data recording. He gives the example of Barclays Bank that had to collect data over six years before it could make assertions justifiable going by the data. Data records stand out as a source of strength.
One cannot fail to mention the integrated technology and applications when mentioning the sources of strength. This refers to technology that goes beyond mere statistics, it involves modelling capacities, simulation abilities and integration of various aspects in the business. Take for instance the Boston Red Sox modelling technology. It goes above mere analysis of on the field performance. It looks at the quality of services at the home ground and maximises opportunities including expansion of sitting place, the quality of cleaners work, among others. The technology in application for an analytics competitor remains fundamentally essential.
Another strength for analytics competitor lies in the cultural mind set in the employees. From the author’s narrative, one gets the feeling that analytics competitors endeavour to carry along the entire employee base in the same wavelength. This limits conflicting interests or objectives. The company is able to approach policy implementation cohesively. As the author mentions, analytics competitor have their optimization and analytical strategies explain to the management their line of thought and back it with facts. The management also approach the concept with an open mind ready to ensure its success. In the long run, internal conflict is effectively diminished.
Influence on my views on quantitative business modelling and its utility in decision making
The article has put across a strong case for the application of quantitative business modelling. Indeed, the author indirectly pours scorn on the use of intuition and guts rather than scientifically proven data. He convinces the audience that even though the application of quantitative business modelling does not necessarily address business concerns in totality, but it attempts to limit errors and position the business strategically. Indeed, the place of business quantitative modelling cannot be overlooked as the author points out. With the progressive results and progress the businesses that have adopted the approach have demonstrated, the author casts aspersions on the ignorance of quantitative modelling and fundamentally convinces the audience with stubborn statistics. On my part, I appreciate the place of modelling in business. Its utility in the market is essential and should not be ignored at all costs.
Conformation of my views in light of other readings
One may want to cast aspersions as to the ethical considerations with the application of the modelling approach. Indeed, from an ethical perspective, the analysis of statistics should have a definite boundary. The approach assumed by the analytics competitors seems to overlook the boundaries and in their desire to obtain information, they may be tempted to get any data in any way. It is my contention that the approach should be revised in line with ethical practises and conduct. Even if in the search of data and information, the process should be within the law and moral behaviour.
One should not be obsessed merely with the numbers but should be objective in meeting the requirement within the ambit of what the law permits. This would be in line with the Christian notion of fairness, honesty and justice for all. Christian philosophy appreciates the presence of competition in markets and insists on application of fairness and justice in competition in the markets. In my opinion, the analytics competitor model is in consonance with the Christian doctrine in as far as the data collection is ethical and the application of the gathered data is equally ethical. In the end, the business and political notion that the end justifies the means must be denigrated and disapproved.
In conclusion, it is imperative to appreciate the place of analytics competition in the modern market. As the author rightly asserts the market has become competitive and business must wring out benefits, however, meagre in the quest to gain advantages over others. Analytics competition offers the solution to the struggle to maintain market leadership using a scientific approach. It also limits the business susceptibility to errors and omissions. In the long run, the company culture is tailored in consonance with modern practises that appreciate the place of scientific technology. One has to appreciate that strategy demands for the application of the best for survival’s sake. The analytics competitor model is currently the best application. As the author observes analytics talent is to the 2000’s what programming was to the 1990’s. The deliberate search for analytics talent in the market attests to its usefulness in the world of business today.
Davenport, T. H. (2006, January). Competing on Analytics. Havard Business Review, 84(1), 98-107.
Davenport, T. H., Cohen, D., & Jacobson, A. (2005). Competing on Analytics. Babson Executive Education, 1-12.
Harfield, T. (2009). Strategic Management and Michael Porter: a postmodern reading. International Journal of Strategic Management, 1-14.
Robinson, C. (2008). Competition and Regulation in Utility Markets. New York: Edward Elgar Publishing.