April 5, 2022

• Getting to better structured and better understood data
• Ensuring that data utilized by data scientists has attribution from the business
• Ensuring data is useful to the business when they receive the output
• Aligning data strategy to answer strategic business needs
• Actioning the proliferation of tools to attain actual value
• Realizing data can be a hub of centralized and operationalized entities if appropriate governance is in place
• Ensuring that you have the team and keep the team in place that can help you grow through data 

Sean MacCarthy

Exec. Dir. Global Analytics & Store Segmentation
Claires, Inc.

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Intelligence must be used to provide value. That principle remains true for artificial intelligence. Global corporate enterprise is certainly benefiting from applied AI. But if that applied AI is not augmented, like any non-useful intelligence, it will be rendered trivial. The goal must be for enterprise AI to continue to evolve.

• Divining your most valuable data based on enterprise and customer needs
• Applying cognitive tools to optimize and augment your most valuable data
• Increasing accuracy as your cognitive automation tools continually learn from your data
• Realizing both large scale and personalized accuracy for your enterprise, workforce and customer

With phrases like ‘data is the new oil,’ there is a general awareness of the value that data can provide. But for global corporate enterprise, a true understanding of the potential value of data must bolster that general awareness. Only with that understanding can a data monetization conversation begin.

• Beginning with the customer value proposition for data monetization
• Realizing the importance of data to your organization’s bottom line
• Knowing that the ultimate value of the data is determined by the quality of the input
• Understanding that data can’t have its highest value unless all enterprise players are bought in on data monetization
• Continually refreshing the enterprise understanding of the customer value proposition

Presentation matters. But presentation isn’t the end goal. The end goal is to provide context, insight and value through presentation.

• Realizing the first step to benefiting from data visualization is data cleansing and processing
• Battling the fact that your output has bias because your input has bias
• Overcoming the democratization of data putting too much on your plate
• Ensuring true insights or at the very least- the path to insights vs. pretty pictures

• Taking the regulatory infrastructure into account
• Creating a walled-garden
• Optimizing managed cloud environments
• Adding governance and controls when the tools are outside of a managed environment
• Treating your tools as efficiency and consistency aids simply to keep pace
• Overlaying decision making prowess for competitive advantage

Laura Guilbert

Head of Analytics
Wisetack

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