Analytical Capabilities

Building a Roadmap to enhance analytical capabilities

Developing analytical capability seems to be straightforward. It is also a fact that most firms have paid close attention to data over the last decade, have sponsored analytical programs, and have attained a higher stage of analytical capability. However, an overwhelming majority of organizations have neither a finely honed analytical capability nor a detailed plan to develop one.

There are many moving parts for developing an analytics-driven organization as it includes software applications, technology, data, processes, metrics, incentives, skills, culture, and sponsorship. Nevertheless, the benefits of becoming an analytical competitor far outweigh the costs. My attempt in this blog series is to introduce a roadmap that describes how organizations can become analytical competitors and benefit at each stage of their development process.

Level 1: At this level, organizations are analytically impaired as they lack consistent and quality transactional data necessary for decision making. Unless the data quality is fixed, organizations should not embark on analytical initiatives as it will not yield the desired results. Dow Chemical’s path is instructive here. It had implemented one of the first SAP systems in the United States in the late 1980s but did not begin serious initiatives to use data analytically until enough transaction data had been accumulated.

Organizations at this stage are analytical aspirants where functional management builds analytics momentum and executives’ interest by applying basic analytics. For example, a utility might use machine learning capabilities to manage its electrical grid but not elsewhere in the enterprise. A company needs a clear strategy to know which data to focus on, allocate analytical resources, and what it is trying to accomplish. Organizations initially focus on one or two areas for analytical competition:

Caesars: Loyalty plus service

New England Patriots: Player selection plus fan experience

Intuit: Customer-driven innovation plus operational discipline

Progressive: Pricing plus new analytical service offerings

To significantly impact business performance, analytical competitors must continually strive to quantify and improve their insights into their performance drivers – the causal factors that drive costs, profitability, growth, and shareholder value in their industry. In practice, most organizations build their understanding gradually over time in a few key areas, learning from each new analysis and experiment. To decide where to focus your resources for the most significant strategic impact, you should answer the following questions:

  • How can we distinguish ourselves in the marketplace?
  • What is our distinctive capability?
  • What critical decisions in our processes and elsewhere need support from analytical insights?
  • What information matters to the business?
  • What are the information and knowledge leverage points of the firms’ performance?

Finally, to ensure that strategy is converted into operational results, organizations must define and monitor metrics tied to strategic enterprise objectives and align individual incentives and metrics with business objectives.

In the next blog, we will see how we bring strategy to execution.

Gopi Kandukuri

Gopi Kandukuri

Gopi is the President and CEO of Saxon since its inception and is responsible for the overall leadership, strategy, and management of the Company. As a true visionary, Gopi is quick to spot the next-generation technology trends and navigate the organization to build centers of excellence. As a digital leader responsible for driving company growth and ROI, he believes in a business strategy built upon continuous innovation, investment in core capabilities, and a unique partner ecosystem. Gopi has served as founding member and 2018 President of ITServe, a non-profit organization of all mid-sized IT Services organization in US.