Meeting Analytics Deployment Challenges

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 these challenges are impossible to meet. It just takes the right strategy to recognize them when they appear 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 meet each one of them to achieve measurable analytics success.

Many companies don’t have a big stable of 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 management is willing to make the commitment to analytics technology, current IT systems may not provide access to the amount, or types, of data required to facilitate complex, in-depth analysis. Finally, management 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 tool sets 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, many companies also face seemingly intractable deployment problems. Even if you have a deployment plan, there’s often a lack of resources available for deployment–especially in those critical 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.

Successful analytics strategies are based on comprehensive development and deployment frameworks that address both business and technical aspects of the analytics initiative. Effective analytics frameworks stress rapid prototyping and decision-making processes 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 good 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 also contain an overall conceptual analytics strategy and a model for analytics integration—both architecturally and operationally.

Your analytics framework should also include methods for aligning your analytics architecture with your business. It address how to implement change within the organization and align your team’s expectations for the system with your corporate strategies and 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.

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