Professional Services and BPO

Use data and AI to manage a growing professional services business.

As professional services and BPO firms add people, clients, geographies, and business units, managing the data across the business becomes more complex, with information spread across multiple systems and reporting processes. We bring that data together so leaders have a consistent view of the business and can use AI to improve workforce planning, operations, procurement, and client service.

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The Challenge of Managing Data Across a Growing Services Business

Different parts of the business can end up working from different numbers.

15%

The share of its internal knowledge and operational data the average professional services firm can structurally access through existing systems. Much of the remaining data is spread across disconnected platforms, local drives, and separate reporting processes.

BPO and professional services firms can grow through acquisitions, geographic expansion, and new client contracts. That growth can introduce new systems, entities, and reporting processes across the organization.

When those systems use different definitions or reporting processes, measures such as headcount, utilization, attrition, and other operating metrics can vary across functions or business units. Reconciling that information takes time and makes it harder for leaders to get a current view of the business.

A governed data foundation establishes consistent definitions and access across the organization. It can also provide the data needed for AI applications as firms introduce them across different functions.

Professional services and BPO firms often add systems and reporting processes as they grow, leaving operational data fragmented across functions. That makes enterprise reporting more manual and also limits how effectively the organization can use that data for AI.

COMMON PROFESSIONAL SERVICES AND BPO APPLICATIONS

What we can build for professional services and BPO teams

Most AI initiatives fail after the strategy deck is delivered. PivotX stays through execution, adoption, and measurable business outcomes because that's where transformation actually happens.

Yours would look different.

Unified HR and Workforce Analytics Platform

Bring Oracle, payroll, Workday, and other workforce data together in a single governed foundation with self-service dashboards and conversational query capability.

Talent Acquisition and Recruiter Productivity Intelligence

Time-to-fill, offer acceptance, sourcing effectiveness, and recruiter performance tracked in one place, giving talent teams a clearer view of where hiring is working and where it needs attention.

Operations Reporting

Reporting across geographies and business units standardized around consistent definitions and metrics, giving leaders a current view of performance across the organization.

Vendor Onboarding Automation

Supplier intake, qualification, duplicate detection, and ESG screening automated to reduce manual work and the time required to onboard new vendors.

GTM Strategy for Data and AI Services

Positioning, offerings, channel strategy, and operating model developed for professional services firms building or expanding their data and AI businesses.

Contact Center AI with Governance

AI agents evaluated against defined measures for performance, compliance, escalation, and resolution, giving teams a way to assess how the system is performing once it's in use.

HOW WE WORK

Growth can change what a professional services firm needs from its data.

We start by understanding how the business operates across its functions, geographies, and business units and what information leaders need to manage it. We then look at the systems and data behind those questions and identify what needs to be brought together. The data foundation is designed to support additional business units, geographies, and use cases as the organization grows. AI applications can then build on that same foundation rather than requiring a separate data effort for each one.

See our full method

Week 1–4

Explore & Evaluate

We map the business and identify where AI could create measurable value. Working with your team, we evaluate potential use cases and narrow the list to the ones worth pursuing. By the end of week four, we know what we're building, why it matters and how we'll measure success.

Week 5-8

Validate

Solution design and prototyping happen alongside user involvement. The people who will use the solution help shape it as it develops. Working MVPs give the team something real to test and evaluate rather than asking them to react to a finished product.

Week 9-10

Value & Scale

We deliver the working AI solution, a validated 12-month roadmap, and a quarterly execution plan. We also begin the process of putting the solution into use. At this point, your team has experience with the solution and a clear understanding of what comes next.

Proof