Four Primary Pillars Of Analytics

Competitive intelligence and analysis is an important part of a business. Competitive intelligence is the art of defining, gathering, analyzing, and distributing intelligence about products, customers, competitors, individuals, concepts, information, ideas or data needed to support executives and managers in making strategic decisions for a business. This includes a broad array from government intelligence to market intelligence to business intelligence (Competitive Intelligence, n.d.).

Competitive intelligence is a great tool to use in marketing research. It is “A systematic and ethical program for gathering, analyzing, and managing external information that can affect your company 's plans, decisions, and operations” (“Definition competitive intelligence“, 2011, para. 2). A company can use competitive intelligence to learn more about their competition and figure out ways to better market to their company against their competition.

Competitive analysis main objective is to research, analyze, and compare the competition in relation to the company. Analytical tools used for competitive analysis include the five forces framework, value net, driving forces, strategic groups, competitor analysis, and key success factors are analytical tools. The competitive analysis will enable the trucking company to understand more about the industry and the competition, to be able to develop a competitive strategy that will give the company a competitive advantage by taking into account the actions and responses of the competitions (Thompson, Peteraf, Gamble & Strickland, 2016).

The four pillars of analytics competition are (1) Support of a strategic, distinctive capability, (2) an enterprise-level approach to and management of analytics, (3) Senior management commitment, and (4) Large-scale ambition (Davenport & Harris, 2007).

In order to be an effective analytical competitor, Davenport and Harris (2007) assert that firms must meet certain prerequisites. Those prerequisites are at least a moderate amount of quality data about the type of business that analytics will support, hardware and software, the commitment of managers to develop analytics, and executive sponsorship (Davenport and Harris, 2007, p.16). Analytics is about extrapolating new information and

In today’s companies, the analytics software plays the important role and guides the future activities to a great extent.

2. Uniqueness - There is no single path to follow to become an analytic competitor, and the way every company uses analytics is unique to its strategy and market position. Accenture 's use of analytics has always been unique to acquire the market position. Accenture, in telecommunication industry uses bundle

* IDS worked with P&G business units, suppliers, customers and external vendors, such as Nielsen and IRI, to collect data about the “what,” “why” and “how.”

The role of the project management office (PMO) has increased nowadays, as many organizations are implementing it. According to PMI (PMI 2011), organizations with a PMO report more projects coming in on time, on budget and meeting intended goals to those without a PMO.

Senior Management Commitment. This trait has been purposefully listed first because without it, the other characteristics will not have the necessary effect throughout the organization. We have already seen that Brian Moynihan, BAC/ML’s CEO, has realized the benefit of using analytics and has described how it can be used to the bank’s advantage. In addition, in an interview with Forbes from 2013 , Cathy Bessant, the head of Global Technology and Operations at BAC/ML, made it clear that data analytics was one of three key areas for growth that BAC/ML has made the decision to invest in. And in many interviews with Ms. Bessant and other high-level executives at BAC/ML we hear the very same message. Hearing such direction from the top ensures that the broader company views analytics as

All business needs to take action which helps them keep good position on the market. Before taken any action analysis has to be made. Answers and data which were obtained during analysis can help chose strategies, which help achieve objectives.

At the beginning, I would like to give some examples of competing on analytics. We all know the how powerful the kill app is (the extremely most successful and popular software). Over the years, groundbreaking systems from companies such as Otis Elevator (predictive maintenance), American Airlines ( electronic reservations), and American Hospital supply (online ordering) have dramatically risen their creators’ revenues and reputations by using these heralded and coveted applications. These applications amassed and applied date in ways that optimized operations and upended customer expectations to unprecedented degrees. Organizations such as Harrah’s, Amazon, Capital one and Boston Red Sox have dominated their filed by deploying

Part 2. How Business Analytics can be used to gain advantage in a competitive marketplace

“Competing on Analytics” defines an analytical competitor “as an organization that uses analytics extensively and systematically to outthink and out execute the competition.”(1) Business analytics is a new way for companies to separate themselves from their competitors. I recently completed an internship at the firm PricewaterhouseCoopers (PwC) and will work there full-time upon completion of this program. PwC uses analytics to help solve complex business issues and to identify opportunities across different industries. PwC is the largest professional service company in the world and is part of the Big Four accounting firms. PwC operates in over 157 countries with more than 750 offices throughout the world.(2) PwC is structured into three service lines, which are Assurance, Advisory and Tax. The assurance practice audits almost 30% of the global fortune 500 companies.(2) The advisory practice is mainly consulting activities that cover strategy, cyber security and privacy, human resources, deals and forensics. (2) These three practices generated $35.4 billion in revenue in 2015. (2)

Operating – ABC has traditionally competed on operating efficiency thus, ABC may not have operating expertise necessary to compete extensively on analytics. ABC needs to create an organizational level of expertise through the implementation of IT architecture, data scientist skillsets, and a comprehensive objective to implement these tools and skills.