Successful Augmented Analytics Initiatives Do Not End with Implementation

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Click to learn more about author Kartik Patel.

The successful implementation of an augmented analytics solution for business users is not just about choosing a cost-effective tool and completing a timely deployment, nor does the process stop with training. In order to get business users to embrace and adopt self-serve augmented data discovery tools, the enterprise must approach the implementation with appropriate change management processes.

If you want a business user or a team to align with the Citizen Data Scientist philosophy, you must engage the enterprise at every level. Senior managers and executives must understand why it is important to build a data-driven business environment and how that environment can help the organization to succeed. The enterprise must require that analysis and data is used in presentations and decision-making, and it must reward this evolution appropriately. Creating Analytics Translator roles within the organization is also helpful. Recognise and organize around this liaison role by allowing power users and those who can build a bridge between data scientists, IT, and the business user base.

If the organization is to get the most out of data democratization and augmented analytics, it must not ignore the importance of change management in rolling out the tools and the process. Making data analytics part of the day-to-day and strategic decision process is key. Making sure that business users have access to the data they need to successfully gather and analyze data and to share, report and publish data is a necessity, and the IT staff, data analysts and managers must be available to encourage and support the use of these tools and to answer questions and clarify usage and processes as necessary.

When data analysis is presented, team managers and executives should take the next step by establishing metrics and assigning actions to staff members to address and improve results, tackle issues or capitalize on the opportunities identified the analytics. In this way, the organization can ensure follow through and embed the analysis process and the data focus within every team goal and objective.

To successfully implement and leverage augmented analytics in the organization, the enterprise and its managers and executives must commit to the daily use of these tools and must assess workflow and processes to incorporate the data-driven philosophy into every process and goal. It must encourage and grow data literacy by transforming business users into Citizen Data Scientists and Analytics Translators so that all team members are comfortable with the tools and the concepts.

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