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Every enterprise is talking about Business Intelligence and Advanced Analytics. Every enterprise has considered the benefits of implementing self-serve analytics across the organization and involving business users in the process. Panel discussions at technology conferences and hallway conversations among executives and IT staff encourage the trend and create anxiety within the organization that has not yet embraced advanced analytics at the grassroots level.
But, before your organization selects and deploys a solution, there are numerous important considerations. Choosing and implementing a solution for advanced analytics and augmented data discovery is not as simple as buying team t-shirts for your company baseball team. If you do not take the time and effort to do it right, your enterprise may spend a lot of money and time on a solution that reaps little to no benefit.
Don't become a failure statistic! Ask yourself this: If you don't know what you need, how can you succeed?
Requirements Planning for Data Analytics
Many organizations are so anxious to get into analytics that they fail to consider the depth and breadth of their needs. While it is true that advanced analytics can help every type and size of business, it is important to remember that YOUR organization is not like any other enterprise. Take the time to develop detailed requirements that consider business user skills, use cases for day-to-day analytics needs and for strategic use, the need for mobile access, scalability, data source integration and other needs. Will you need the flexibility to customize or personalize dashboards? What kind of training or guidelines will your organization need in order to access and leverage the analytics solution and provide the kind of results and user adoption you expect? What kind of statistical data, report capability and security will you need? How will you manage growth?
Curated Data Provides Answers, NOT More Questions
Nearly every organization is overwhelmed by the volume of data and the number of disparate sources and data structures it must manage. Your business users, data scientists and IT staff NEED data, but they need the right data and they need to easily integrate and manage that data if they are to use it to their advantage. One of the crucial success factors for advanced analytics is to ensure that your data is clean and clear and that your users have a good understanding of the source of the data so that they can put results in perspective. Social BI and the advent of smart visualization, augmented data modeling, self-serve data preparation makes it easy to gather and analyze the data but insight and perspective is key to success. Be sure to consider the location, condition and accuracy of your data and to select a solution that will connect various data sources (personal, external, cloud, and IT provisioned). Your organization can enjoy an interactive view and clean, clear data so that it is easier to use and interpret to provide data quality and clear watermarks to identify the source of data.
Data Governance and Self-Serve Analytics Go Hand in Hand
Many businesses step away from the concept of self-serve analytics because they believe that the concepts of self-serve and data governance are at odds but nothing can be further from the truth. If you select the right solution, you can ensure data and personal security and provide appropriate access at all levels of the organization. Give your business users the access they need with streamlined data governance to balance provisioned/approved data sources, watermarked/certified data and user-created data while assuring data provenance and dependability. if a user has access to an advanced analytics solution that integrates and delivers data from multiple legacy, best-of-breed and ERP systems, with the right solution, the enterprise can decide what type of data and access each user is entitled to enjoy. You need to understand your governance requirements and goals and select a solution that is flexible enough to deliver access to the type of depth of data your users need.
Collaboration Results in the RIGHT Analytical Solution
We already discussed the need for detailed requirements but it is also important to point out the importance of involving all teams in the requirements process. Business users will have different requirements from data scientists, IT staff and executives. If you are to succeed in implementing and leveraging an advanced analytical solution, you need to understand the perspective, role and needs of each group and select a solution that will meet those needs, one that is flexible enough to accommodate changing requirements, location and organization growth, and the organizational goals for cost and project timelines. Don't make assumptions. Collaboration among users and teams is key to your success.
Data Analytics Literacy MUST Exist at All Organizational Levels
Finally, it is important to include data literacy considerations. This does not mean that your users have to become skilled data scientists. It simply means that, if users at every level of your organization are going to adopt and effectively use advanced analytics to meet enterprise goals, each user must understand:
- The objectives and goals the organization has set forth for the advanced analytics initiative
- How this initiative impact their role
- How these tools can provide meaningful assistance in helping them to achieve THEIR goals.
- How individuals and teams can share advanced analytics and create a social BI environment
- How advanced analytics and metrics can and will reveal answers, issues and opportunities
- How and when to involve IT and data scientists when strategic, next level, analytics is required
- The guidelines and basics of the advanced analytics environment, e.g., various data sources, reports and types of analysis available for their use
When we talk about data analytics literacy, we must include literacy goals at every level of the organization, including senior executives. Team members are more likely to take this initiative seriously if senior executives use and understand these tools and can engage in meaningful discussions when presented with reports or when discussing issues or opportunities revealed by data analytics.
This article provides a summary discussion of some of the important factors involved in the consideration of an advanced analytical solution implementation. This planning process is key to the successful selection, implementation, deployment and management of an advanced analytical solution.
