An Analytics Capability Landscape

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I have recently completed some research on the increasingly broad portfolio of analytic capabilities available today. These capabilities range from traditional Business Intelligence (BI) capabilities like reporting and ad-hoc query to modern visualization and data discovery capabilities as well as data mining and advanced analytics.

Organizations today are turning to these analytic capabilities to drive decision-making. But with the different types of decisions that need to be made, multiplied by the different types of analytic capabilities available, it can be difficult for organizations to choose the right capabilities for the situations at hand.

While there seem to be as many reasons for adopting analytic capabilities as there are organizations adopting analytics, the reality is that three key business needs are driving analytic adoption:

  • A need to report on some aspect of the organization
  • A need to monitor the organization’s behavior or performance
  • A need for the organization to make data-driven decisions

Analyzing these business needs reveals a couple of interesting points. First, acting on a report is a decision-making scenario, not a reporting one. Similarly, taking action on the basis of what is seen (or projected) on a dashboard is a decision-making scenario, not a monitoring one. Decision-making it turns out is the critical issue for analytic capabilities.
Organizations make many different kinds of decisions – from infrequent but large-impact strategic decisions to regular tactical decisions involving management and control as well as large numbers of operational decisions surrounding individual transactions or customers. Analytic capabilities play a role in all these decision types. Ultimately, any analytic capabilities used by the organization must align with business needs, be geared toward the intended user, and support decision-makers, both human and automated.

However, analytic capabilities are often presented as part of a maturity curve, where enterprise customers are expected to keep moving “up” the curve to get more value. My research suggests that enterprises adopt these technologies in different sequences and ultimately need a mix of these capabilities. Most, if not all, enterprises have a real business need for all of them.

The research found that roles across the organization are using analytic capabilities, and different departments need different approaches. The report discusses how to choose analytic capabilities with a decision-led, role-centric, and style-based approach:

  • Decision-Led in that analytics capabilities are selected with a clear view of the decisions to be made using those capabilities.
  • Role-Centric because decision-making problems can be solved in a variety of ways and the people who will be involved will further constrain and direct the type of analytic capability to be used.
  • Style-Based because analytic capabilities vary in terms of their interactivity, presentation style and approach to scaling.

The research draws attention to the different types of analytic capabilities, the different roles in an organization that use analytics to drive decisions, and most importantly, the different categories of decisions that must be made within an organization.
This research was conducted by Decision Management Solutions and sponsored by Actuate and FICO to examine the different types of analytic capabilities available to organizations and the business situations for which they are most appropriate. It is now published as a report - The Analytics Capabilities Landscape Research Report  - and an associated Infographic. You can download this free report and infographic from Information Management. I hope it will help your planning and purchase decisions now and in the coming months.

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