A hiker at the top of a mountain, looking into the distance as the clouds engulf the mountainside below.

Analytics Strategy

Strategizing for analytics success.

  • Nexus Cognitive Chief Executive Officer, Anu Jain
    Anu Jain

In my last blog, I talked about Analytics Ops and embedding analytics in your corporate DNA. It's a critical factor in achieving analytics success, but it's not easy — by any means. There are several challenges that you'll need to overcome along the way. Fortunately, none of those challenges are impossible to meet. It just takes the right strategy to recognize the challenges and develop an effective approach to overcome them.

Business, architectural, and deployment challenges in developing an embedded analytics culture are myriad. These issues often derail analytics initiatives before they get started, and you must each one of them to achieve measurable analytics success.

Many companies don't have IT people who are deeply knowledgeable about analytics and how to deploy analytics capabilities — especially at scale. Further, even if there are folks who possess analytics knowledge, management may not feel that they can expend the money on what they see as a high-dollar project with specious chances of success.

Also, even if they are willing to purchase analytics technology, current systems may not enable access to the amount, or types, of data required to facilitate complex, in-depth analysis. Finally, management — if they have little experience with analytics — may not understand how to fully translate the insights provided by analytics systems into true operational improvement.

Architecturally, many companies struggle to make sense of the complexity and range of choices of analytics toolsets available to them. This is often exacerbated by the presence of existing tools and silos of technology within the organization. People are also often hesitant to embrace change. These problems are again made worse by the pressure to deliver the analytics initiative quickly, and at optimal TCO.

Once the business challenges have been addressed, and they've developed what they believe is a sound analytics infrastructure, many companies also face seemingly intractable challenges when they're ready to deploy their newly minted systems. Even with a plan in place, there's often a lack of resources available for deployment and those critical, initial several months after rollout. Typically, there's also a fair amount of uncertainty over whether the system will be powerful enough to provide the insights management demands, and whether the system will be flexible and scalable enough to change and grow as the business grows and needs change.

All these challenges are difficult, and it's critical to address them to achieve a successful analytics deployment, but they're not insurmountable. To overcome these challenges, you need a comprehensive analytics strategy that successfully addresses the business, architectural, and deployment issues you'll face.

Sound analytics strategies are based on comprehensive development and deployment frameworks that address both business and technical aspects of the analytics initiative. Successful analytics frameworks are those that stress rapid prototyping and decision-making that will deliver high value and impact to your organization and that set you up for sustainable success. These frameworks generally cover four areas:

  • Design
  • Alignment
  • Value creation
  • Evaluation metrics

A sound analytics framework will provide you with a roadmap to achieve your goals. It will contain milestones and rapid-development methodologies to create quick-win deliverables that are unique to your organization. The roadmap should contain an overall conceptual analytics strategy, a model for analytics integration — both architecturally and operationally; strategies to address change management; and strategies to develop a performance management matrix that enables you to measure success.

Your analytics framework should also include strategies for aligning your analytics architecture with your business — in terms of your expectations for the system and how the infrastructure will be built to support your expectations. The alignment portion of the framework should also address how to manage change within the organization and align your team's expectations for the system with your goals and with the reality of what the system is designed to deliver.

In addition to aligning the reality and expectations for analytics, your framework should also outline how the system will create value for your organization. It should answer questions such as, "What are the industry best practices that we can leverage to really get us focused on using analytics to create value for our company?" and "How can we best use the tool(s) we've selected to provide us with the insight we require?"

Speaking of insight, the only way you'll know if you're achieving your goals is if you have a quantitative measurement system in place. A thorough analytics framework will help you develop these metrics. Your metrics shouldn't be pre-defined; they're unique to your company. Beware of vendors that have all the metrics defined up front for you. You need to measure what makes you successful, not what makes other companies successful.

If you have the proper analytics framework in place, you can overcome the challenges you'll certainly face, and you can deliver sustainable success with your analytics initiative, no matter what your goals are. Remember, the bottom line is that analytics serves one purpose: to derive more actionable insights and deliver the ability to act on those insights to deliver continuous business value.

Feb 19, 2021