Senior Manager Strategy, Planning, Operations (SPO) – Analytics & Insights

ServiceNow•Santa Clara, CA

9d•$165,500 - $289,600

About The Position

ServiceNow is seeking a Senior Manager, Analytics & Insights, within the Strategy, Planning, and Operations (SPO) team’s Central Strategy organization. The Analytics & Insights pillar leads analytics for the Customer Excellence Group (CEG), turning data into insights that strengthen customer health, accelerate adoption, and inform leadership decisions. The team owns CEG executive scorecards, OKR metrics and targets, corporate OKR and SPM reporting, and Quarterly Impact Insights, while supporting the AI Command Center, Global Forecast Call, and Mission Control. This is a hands-on individual-contributor role with no direct reports. The Senior Manager is accountable for the accuracy and narrative of executive reporting and uses it to identify emerging issues, connect signals across reporting streams, determine where deeper analysis is warranted, and develop models and recommendations. The role partners across product, engineering, sales, marketing, finance, and customer success to drive decisions and follow-through. Recurring reporting is an important part of the work and serves as the foundation for setting and advancing the analytical agenda.

Requirements

8+ years of experience in investment banking, private equity, management consulting, strategy and operations, or technology-company analytics leadership, with rigorous analysis and executive decision support central to the work.
Advanced Excel or equivalent, with demonstrated experience building financial or operational models that informed an executive decision.
Ability to structure ambiguous problems, identify meaningful signals in recurring metrics, and recommend a course of action.
Strong written, verbal, and presentation skills, including the ability to influence senior leaders through clear storytelling and analytical confidence.
Experience working in a matrixed environment, aligning stakeholders, and following through on recommendations without direct authority.
Ability to own recurring reporting with high accuracy and use it as a starting point for deeper analysis.

Nice To Haves

Experience owning executive scorecards, OKR or operating-metric reporting, or quarterly business reviews.
Power BI experience and experience with cloud data warehouses such as Snowflake.
Working knowledge of SaaS business drivers such as adoption, renewal, and expansion.
Experience using AI to improve analysis, decision-making, or operational processes.

Responsibilities

Own CEG executive scorecards across global, geographic, and major-area views, including explaining changes, causes, and recommended leadership actions.
Define and maintain CEG OKR metrics and targets, as well as adoption and downsell reporting.
Run the corporate OKR/SPM reporting cycle with metric owners and reconcile figures across scorecards, OKR submissions, and executive materials before leadership review.
Own the analysis and executive narrative for Quarterly Impact Insights, partnering with Finance on underlying data.
Contribute account-level analysis and metrics to the AI Command Center and Global Forecast Call; stay informed about the weekly D&L forecast and Partner 360 ROI and connect them to analyses.
Review reporting cycles for emerging risks, anomalies, and open questions, and determine which merit deeper analysis.
Structure ambiguous problems, develop hypotheses, and build driver-based models and scenarios that quantify stakes and potential outcomes.
Deliver strategic analyses with a recommendation, a named decision-maker, and agreed next steps.
Turn recurring ad hoc requests, including Impact coverage analysis and account enrichment for undeployed backlog work, into planned analyses.
Drive follow-through with cross-functional partners and influence without direct authority.
Reduce manual consolidation using automation, standard templates, and consistent metric definitions across reporting streams.
Recommend reports and metrics to simplify, combine, or retire based on leadership use.
Apply AI where it improves analytical speed or quality and critically evaluate where it does not.