The 5 Pillars of Digital Analytics Transformation, by Greg Dowling
pillars
Digital Transformation has been a hot topic in enterprise strategy for over a decade, however most organizations are struggling with one of the key elements of this transformation – how to effectively measure and optimize digital customer experiences.
Driving digital transformation at the enterprise level requires not only the realignment of business models and strategies to embrace digital technologies, but also the execution of customer experience engineering to engage and delight customers at each and every touchpoint in the customer experience lifecycle – both digital AND non-digital.
Measuring the customer experience in both quantitative and qualitative terms has historically been a challenge to most enterprises. Efforts to maximize the use of customer data to optimize and enhance the customer experience often result in data siloes focused along specific channels of customer interaction. For example, call-center optimization that does not take into account web channel usage, social media sentiment, or qualitative customer feedback does not provide a complete picture of overall customer experience and satisfaction.
To enable digital transformation, focused on optimizing all customer experience touchpoints, enterprises should adopt a comprehensive measurement strategy based upon the Five Pillars of Digital Analytics Transformation:
Digital Analytics Infrastructure: Enterprises must enable robust and scalable data capture across all digital touchpoints. Invariably this requires a certain level of automation to ensure consistency across all deployed assets and customer touchpoints, but at a minimum should be based upon a documented standard with continual monitoring and alerting. Integration with existing IT processes and quality assurance will enforce adherence to data collection standards and increase overall robustness of data.
Organizational Governance and Process: The formation of a dedicated Analytics Center of Excellence is essential for enterprises seeking to leverage data as an asset – ultimately driving successful digital transformation. The CoE as an organization is responsible for defining the governing standards, processes, and best practices for effective utilization of data, fostering knowledge sharing and supporting data-driven decision-making. Additionally, the CoE serves as the training hub and overall data steward and champion garnering senior leadership support and advocacy.
Information Technology Infrastructure: Enterprises must ensure that the underlying business intelligence technology infrastructure is adequate to support data collection and optimization across all customer touchpoints in order to drive and support digital transformation. More importantly, the business intelligence technology infrastructure must support the integration of customer data (qualitative and quantitative) collected across all channels into a central enterprise data warehouse replete with the necessary data analysis and statistical modeling tools.
Data Visualization and Democratization: Data-driven decision-making empowers digital transformation at successful organizations. The ability to make complex information ‘obvious’ and deliver this information to the right person at the right time enables enterprises to make fact-based decisions around customer experience optimization. For maximum effect, organizations should establish focused measures of success (KPIs) aligned to specific business units and customer segments, coupling this with advanced data exploration and self-service capabilities.
Customer Analytics Learning Agenda: Enterprises must establish and execute a formal learning agenda that outlines the approach, techniques, and delivery of high impact analysis projects. These advanced analysis projects should be focused on generating actionable insights in support of a digital transformation strategy. A learning agenda secures organizational commitment to perform these advanced analyses and provides a visible roadmap of insights allowing for prioritization, senior leadership support of the analytics learning agenda, and funding by supporting business stakeholders.
Digital transformation is much more than investing in digital technology; it is the realignment of business models to support the new digital economy and effectively engage digital customers at every touchpoint in the customer experience lifecycle.
Enterprises lacking a comprehensive measurement strategy aligned with the Five Pillars of Digital Analytics Transformation will be unsuccessful at optimizing the user experience and unable to realize the benefits of their investments in digital transformation.
After all, you can’t improve what you don’t measure…
