For B2B marketing and sales executives, the question isn’t about whether they’ll invest in predictive analytics in 2016, but rather how to do so intelligently and in a way that fits with the needs of their organization. Building a data-driven, revenue engine starts with an understanding of your organization’s current level of analytics proficiency.

This is where the SiriusDecisions Analytics Proficiency Assessment Model comes in. The model summarized below will help you understand where your organization is technologically and culturally and what changes and investments are necessary. You can take the self-assessment now or read on for a sneak peek at the 5 essential criteria you should rate your company’s proficiencies against. Once armed with this information, you can evolve your organization’s use of analytics, moving beyond simple measurement and reporting, to exploratory and predictive analytics capable of guiding strategy and execution.

  1. Planning for Analytics Success

Is your planning process reactive or integrated and continuous? The most sophisticated and informed companies are increasingly using analytics to explain and predict performance and facilitate their decision making. As your organization becomes more advanced with analytics, sales and marketing can align and concentrate on the data to improve business processes and overall team performance. Businesses that optimize analytics to the fullest will continuously rely on the numbers to help drive change, seek new opportunities and identify the best ways to improve efficiency and results.

  1. Proper Processes in Place

Does your company consistently and uniformly analyze projects? Are your analytics reporting processes siloed and manual? These are the kind of questions you should consider when you evaluate the varied processes that enable any necessary on-demand and periodic analysis. Marketing and sales teams that excel in this department boast an analytics process that is cross-functional and unified at all levels of the organization.

  1. Skills and Tools to Excel

This criteria points to an organization’s ability to use people and systems to plan and execute analytics efforts. Do you have adequate quantitative talent? Does that talent have necessary training? These are two very different questions – while your personnel may have the quantitative skillset, their efforts are too often futile if there is no proper training on effective sales and marketing analysis and reporting in place. By and large, the companies that excel at this are ones that prioritize awareness and understanding of the range and capabilities of advanced analytics tools and services available internally.

  1. Data Driven Not Data Deluded

5Is your data inconsistent and siloed, or is it adaptive and readily available for your decision-making process? Data is like the gasoline for the analytics car – you need it to fuel properly! The quality of insights you can yield from your analytics efforts hinges on your data availability and quality. The most advanced data-users have an expanding and adaptive data management environment and a technological infrastructure that supports large volumes of data. For many organizations, the data management challenge increasingly focuses on managing volume and velocity, and determining how to dispose of data after it is used.

  1. Cultivating Corporate Culture

How does your corporate culture respond to the idea of data-driven marketing? Is it met with resistance or enthusiasm? Perhaps it falls somewhere in between or has rarely been considered. Nevertheless, an organization cannot be truly analytically proficient (nor benefit from analytics) until it is equipped to implement the necessary changes revealed by its analytics efforts. This starts with culture. Companies that are more open to data-driven marketing and believe in decision making powered by data better reap the advantages analytics offers because of how they respond to the results. Companies with data-driven cultures are more receptive to applying and integrating analytics cross-functionally and are quicker to transition quantitative results into more efficient and effective real-life practices.

With this gained insight into the state of your organization’s analytics proficiency, it may be time to check out The Comprehensive Guide to Predictive Intelligence to better educate yourself on how predictive is empowering B2B decision making with unrivaled time-sensitive data-driven insights.