Summary
In the ever-growing business world, competition has become so stiff, hence requiring one to be an analytic competitor. To use sophisticated data collection methods, employ decision makers and make analytics part of their competitive strategy. To become an analytic competitor, several ideas must be put into practice. These include championing analytics from the top, creating a Single analytic initiative, focusing attention on analytics effort, establishing an analytics culture, hiring the right people, and using the correct technology (Davenport, 2006).
As part of their dominant strategy, analytic competitors have coordinated ways such as having their top positions in the company led by skilled and outstanding leaders, employing decision-making techniques at every level, hiring employees with expertise and deploying the best quantitative tools. These tools are subsidized by the best technology.
Anatomy of Analytics Competitor
The anatomy of an analytic competitor can be broken down to three attributes that encompass the organizational structure. To begin with, there is modeling and optimization to identify the most profitable customers and those with a likely higher profit potential. The second attribute is to use an enterprise approach in business functions to replace ancient techniques of marketing with more quantitative ones. Finally, employing senior executive advocates with skills to change the behavior, processes and culture of the organization in meaningful ways (Davenport & Harris, 2007).
Their Sources of Strength
Analytic competitors have directed their energies towards things that matter most. These include: Building the correct culture, finding the right focus and hiring the right people. To achieve the right culture and focus, analytic firms pursue the best people—those with the ability to simplify complex ideas and are amassed with relationship skills to interact well with those who make decisions. In conclusion, the right technology is needed for this: a good data strategy, a computing hardware and a business intelligence software (Davenport, 2006).
Recommendation
Incorporating visual analytics can also prove to be advantageous since, contrary to programming languages, they are more reliable and flexible when manipulating data. When it comes to Human-Driven changes, a lot of time and resources has to be focused on decision-making. An analytic firm should have a management headed by the best decision makers. In analytics, the best technology, tools and resources are only as good as the leader who makes decisions on how they are to be used. Good decisions, therefore, need to be employed and the right actions to be taken. Managers, therefore, need to be well educated on analytic processes that involve making decisions and how to review, analyze and evaluate key decisions (Chen et al. 2011).
In line with the human and technology changes, Strategies used should also be altered to a certain degree. For instance, firms should focus substantial attention on the new ways devised to deal with certain aspects. These should see analytic firms going to new measurement frontiers to ensure their objectives are achieved.
References
Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business Intelligence and Analytics: From Big Data to Big Impact. MIS quarterly, 36(4), 1165-1188.
Davenport, T. H. (2006). Competing on analytics. harvard business review, 84(1), 98.
Davenport, T. H., & Harris, J. G. (2007). Competing on analytics: The new science of winning. Harvard Business Press.
Nelson, G. (2007). Introduction to the SAS® 9 Business Intelligence Platform: A Tutorial. In SAS Global Forum.
Trkman, P., McCormack, K., De Oliveira, M. P. V., & Ladeira, M. B. (2010). The impact of business analytics on supply chain performance. Decision Support Systems, 49(3), 318-327.
