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Are Your Analytics Tight Fit or Loose Hanging?
Michael Lock
DEC 30, 2015 13:20 PM
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Are Your Analytics Tight Fit or Loose Hanging?

 

Close-up Of Hands Holding Digital TabletDoes your sales director really need sophisticated predictive analytics? Do your product managers have any use for financial budgeting and forecasting? Will your data scientists be satisfied with rudimentary dashboard and reporting capabilities?

Amid growth in the analytics space these days, it’s easy to get caught up in the allure of next-generation technology and what it can do for organizations. However, companies that stay focused on the analytical needs of their users and align the tools accordingly are dividends from those efforts.

recent Aberdeen report explored this concept of relevant analytics, and demonstrated how these organizations, in addition to enjoying a variety of tangible benefits, also shared several common characteristics that help them perform.

1. Support From Mahogany Row

Analytical implementations can certainly start as grassroots movements from plebeian business managers, but without executive-level engagement, most of these initiatives die on the vine. Moreover, in top-performing organizations, the executives not only support the initiatives, but get personally involved as champions spearheading an enhanced level of analytical activity. This approach helps ensure political support for implementing the right technologies with the right user groups, contributing to more relevant analytics.

2. Collaboration With Control

Relevant analytical capabilities depend on a foundation of relevant data. This implies that the data is broadly accessible to accommodate requests from multiple areas of the business, but also that it is delivered with high quality standards. Companies that have achieved an elevated degree of relevance with their analytics are more inclined to share information across functions, but with a reasonable amount of governance and oversight to ensure proper usage.

3. Continuous Improvement

Adoption and engagement in analytics is a two-way street. On one hand, companies need to provide their users with capabilities that fit the needs of the job role, are easy-to-use, and relevant to the core decisions of that area. However, the users themselves are not without responsibility in this equation. Top companies take it upon themselves to hire analytically inclined employees, but they also make the effort to train and nurture analytical talent in-house. This approach enables them to leverage the basic analytical toolsets, and positions them to utilize some slightly more advanced and involved technologies as their skill levels increase.

The Perfect Analytical Fit 

Leaning on these foundational capabilities, organizations enjoying relevant analytics are able to bring analytical thought and activity into more areas of the business, and impact a broader variety of business decisions. The research proves this in demonstrating that these companies are much more likely to report strong or pervasive analytical usage in several core areas of the business:

Figure1

From marketing and sales to finance and operations, analytical relevance is a critical component of a Best-in-Class strategy.  These companies are able to drive greater adoption and engagement in analytics across more functional areas, reducing the cost-per-user of the technology, and improving the return on investment as well.

Data-driven decisions are appealing to just about all of us, and why not? We all have some form of experience and gut instinct when it comes to our business, but augmenting that with timely and relevant data can be extremely helpful. Too many organizations fall into the trap of technology for technology’s sake. In other words, spending money, time, and significant effort deploying a solution that looks good on paper, but then wallows in underutilization as “shelfware.”

At the outset, today’s most savvy, forward-looking organizations take great care of these implementations to make sure that the capabilities they invest in are well-matched to the specific needs of the business users. It’s not always possible or reasonable to expect a perfect fit, but the companies that try are rewarded with more efficient decisions and enhanced performance.

 

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