The continual value assessment
OCIRIS GLOBAL
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In this new article we explore some innovative techniques for continually comparing expected and realized value, with a focus on driving proactive:
Concept: Implement routine “Value Calibration Meetings” that include key stakeholders (such as service owners, customers, and financial analysts) to review realized value against expectations.
Unlike standard performance reviews, these meetings would apply scenario analysis to test future adjustments against current value metrics, helping proactively recalibrate value expectations in light of potential business changes.
Concept: Create a DVA tool that could leverage AI or machine learning to analyze historical and real-time data, detecting trends or divergences between expected and realized value.
By integrating with ESM and ERP systems, this tool could autonomously suggest value level adjustments, such as redefining certain Key Value Indicators (KVIs) or Value Level Agreements (VLAs) based on usage patterns or customer feedback.
Concept: Develop an index that quantifies the alignment of realized value with proposed value, scoring areas that meet, exceed, or fall short of expectations.
This index could create a single metric for immediate visual feedback on how well value levels align with targets, serving as a quick gauge for leadership to make decisions about adjustments or interventions.
Concept: Set up alerts for any “value drift,” where realized value starts trending away from expectations.
These alerts, triggered by early indicators like dips in customer engagement or prolonged ticket resolution times, would automatically prompt teams to review and adjust value expectations. Integrating with the DVA tool, the system could even provide suggested actions.
Concept: Adopt a quarterly sprint model focused solely on adjusting value levels in line with recent data. Each sprint ends with actionable adjustments to VLAs or KVIs.
Inspired by agile sprints, these value sprints bring focused intensity and cross-functional collaboration, making value adjustments part of a predictable cycle.
Concept: Develop a live dashboard that visualizes both proposed and realized value metrics, overlaid with any adjustments over time.
With real-time tracking and historic comparison, the dashboard could highlight any time periods where adjustments were made, along with outcomes of those changes, building an institutional memory around value adjustments.
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Sentiment-Driven Value Adjustment
Concept: Integrate customer sentiment analysis (e.g., from social media, surveys) with KVIs to dynamically adjust value levels based on changing expectations or perceptions.
This would make value levels more responsive to the intangible aspects of customer perception, beyond traditional metrics.
Concept: Hold workshops every six months to model and stress-test the current VLAs and KVIs under various scenarios (e.g., economic changes, customer base shifts, or new tech).
These workshops would anticipate potential changes in realized value under different conditions, leading to preemptive value adjustments that ensure resilience and flexibility.
Concept: Build an ECI module into every major process or service, focusing on automatically comparing expected and realized values at critical stages.
ECI modules embedded in processes would allow for real-time data gathering, analysis, and adjustment suggestions on the spot, making continual improvement an integral part of daily operations.
In a next article we will describe the sources of information for the value expected. Stay tuned...?
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