Data Engagement takes the power of traditional enterprise reporting, combines it with modern business presentation formats, and automates the creation and distribution of content to be shared with specific/targeted audiences in your organization. It is an end-to-end data visualization and distribution strategy that helps enterprises leverage critical data to drive positive outcomes. A practice and method to precure, isolate, and correlate data gathered from a single source or multiple sources to help key stakeholders better understand and make critical business decisions.
Partial/Problematic Data Engagement: The PMO team provides project status reporting to key stakeholders on five ongoing IT projects. Each project has a baseline project plan with tasks, milestones, resources, costs, and dependencies. The Program Manager and all Project Managers meet weekly with stakeholders. Each provides a key status report derived from multiple systems via export/import into Power BI.
The data is combined with the imported baseline project information and key resource timesheets for final stakeholder presentation. The baseline project data is three days old. Resource timesheet data is extracted from the prior week. Risk assessment and contingency planning is ad-hoc (debated in each status meeting). Stakeholders’ confidence is waning and discussions regarding on-time delivery, deliverable quality, and budget numbers are raising risk flags. Reports are missing a reliable, single source of truth. Accurate and timely project status reporting is questionable and predictable project outcome is at risk.
Reactive Data Engagement: The Customer Support department receives a series of calls and/or emails regarding a possible product defect. This is documented in a support system which leads to a defect dashboard flagging the product risk chart with an abnormally high number of contacts. This information is funneled to the Product Manager who determines a corrective solution. There are no real-time results, no process-to-resolution predictability, and no measurable outcomes to assist in the process of product improvement.
Static/Disengaged Data Engagement: The Quarterly Sales Review report highlights a drop in district sales where Account Manager turnover is high. Sales management has engaged a new placement firm to participate in sourcing, assessing, and placing new Account Managers for this district.
The District Quarterly Sales Review does not provide historic sales trends associating marketing channels, advertising spends, and sales performance. The district marketing and advertising spend was reduced 50% one month prior to sales reduction discovery. This information is warehoused in an alternate data silo. Sales Department decision and outcome is clouded by incomplete, aged, or missing marketing spends. A single source of truth is required to identify risks and produce a desired department assessment to lead to an improved engagement outcome.
Use Case Silos: Common data engagement reporting may only reflect information from finite use cases. A data silo in an IT Services department without key engagement data from critical customers can skew reporting results. This can lead to frustrating, incomplete, and inaccurate outcomes with incomplete data engagement.
Data Management vs. Driving Outcomes: Enterprise systems have reached a legacy maturity level to efficiently persist, accumulate, manipulate, and report to provide insight to a wide range of departments, divisions, and business units. Relational database systems, No-SQL, data warehouse, data lakes, and dedicated business management systems provide aged responses that can lead to less accurate decision processes.
These systems cannot provide rapid-scale enterprise and data-driven outcomes that are performant, flexible, and accurate. Next generation data engagement must become a priority to take the enterprise to a higher level of data-driven outcomes.
Modern Data Engagement Requirements: Today’s flexible, schema-less data types require next generation, intelligent data stores. Rapidly changing business dynamics demand real-time, absolute-accurate single sources of truth with agile change management for short and long-term enterprise success. They must leverage and present applicable and actionable communications to every critical recipient in the enterprise. They should embrace the following:
Today’s data engagement standards are embracing the entire end-to-end process for enterprise digital transformation engagements. These standards must include critical tools to insure accurate, actionable, agile, data-driven decisions producing critical outcomes for every dynamic, next-generation enterprise.
VividCharts—an Elite Technology Partner— is the next generation data engagement platform for ServiceNow. Get your enterprise more engaged with vivid data today!
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