Placing Your Bets on Analytics
How analytically competitive is your company? For decades, Big Data and analytics have been used in all elements in business. Sticking with intuition-based decision-making in the current technological climate is the equivalent to betting on a horse because of a clever name or the color of its silks. You may get a winner on occasion but rarely do you hit the trifecta. Your results improve when you have measurable data: who sired the horse, who trains it, and how it performs on certain tracks.
Descriptive analytics lets you dictate your company’s fate instead of reacting to it. It should be the foundation for organizational decisions across all departments. CIOs who are leaders in their fields are 92% more inclined to use analytics for organizational decisions than their standard market counterparts. Not choosing to use descriptive analytics makes your organization more vulnerable to one coming up from behind and passing you on the flanks.
There are five levels of analytical competencies used to measure the level of data-based decision-making in an organization.
- Analytically Impaired
- Organizations that are analytically impaired are negligent to the realization that technology is the future of business semantics. These companies have access to customer information but do not track relevant data. They are dismissive of the idea that consumers demand a more personalized approach in both acquisition and relationship management. These companies have a stagnant way of thinking and an inability to make a dynamic adjustment. Regardless of scale or business type, B2B or B2C, the lack of cultivation of user data will idle organizational growth, especially in this technological climate.
2. Localized Analytics
- Localized analytics tracks rudimentary data but the information is limited to the department unit tracking it. There is an acknowledgment in certain divisions of the benefits of descriptive analytics yet inability to use it across the whole organization. This leads to duplication of information by different departments, embarrassing redundancies, and a poor end-user experience.
3. Analytical Aspirations
- Companies who are defined with analytical aspirations are conscious of tech trends and how they apply to business, have buy-in at senior levels, and are taking steps to standardize the governance of data across all departments. These organizations have the best intentions and, as spectators, we are waiting to see how they implement their plans of moving forward and their investment in data tracking systems.
4. Analytical Company
- An analytical company is the penultimate level of profiting from analytics. They have a more advanced approach to descriptive analytics across all facets of their organization compared to an analytical aspirations company, but their efforts are not quite as fortified as an analytical competitor. There is an overall understanding of the organization’s mission and strategy, full integration of analytics and tech components throughout the organization, as well as a well-maintained database central to decision-making from the senior level staff. They are on the right track but are still missing the cohesive and full integration of analytics in everyday organizational tasks.
5. Analytical Competitor
- Analytical competitors are the trailblazers for the application of descriptive analytics and data-based decision-making. They are dynamic in their investment of system technologies to support in-depth advanced analytics and implemented it in every component of the organization. The clean, high quality mined data is application to relevant projects focused on a clearly defined organizational strategy. Data science -based decisions are second nature to these organizations, and they are on a constant quest to ensure proper governance and application. These organizations are information-rich and stay ahead of the ebb and flow of their respective markets.
Large conglomerate or small independent organization, if you are producing goods/service to a client, you can harness the benefits of Big Data and analytics to manage information and create better quality integrative exchanges. The critically missing piece for most organizations is understanding consumers. Consumers are leaving their digital DNA all over the IoT (Internet of Things). They are demanding a customized experience from initial introduction to relationship management. They are more savvy and technologically adept than ever and they know that if you do not deliver on what is important to them, someone else is willing to learn. They will trade you in for the better experience and leave you fading in the stretch.
 “A Very Short History of Big Data” Press, Gil Forbes 2013
 IBM CIO Survey 2016
 Competing on Analytics: The New Science of Winning; Davenport, T. and Harris, J. 2007