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Director of Operations

Develop operational talent and succession plans

Enhances◐ 1–3 years

What You Do Today

Identify high-potential operations leaders, create development plans, build succession depth for critical roles, and ensure knowledge transfer from senior operators.

AI That Applies

Talent analytics — AI identifies high-potential indicators from performance data, learning agility assessments, and project outcomes to surface hidden talent.

Technologies

How It Works

The system ingests performance data as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output is a recommended plan or schedule that accounts for the identified constraints and optimization criteria.

What Changes

You discover that the quiet supervisor on third shift has the strongest improvement project track record in the plant. Data surfaces talent that visibility bias would miss.

What Stays

Developing leaders — giving stretch assignments, providing coaching, building confidence — is entirely human.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for develop operational talent and succession plans, understand your current state.

Map your current process: Document how develop operational talent and succession plans works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Developing leaders — giving stretch assignments, providing coaching, building confidence — is entirely human. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Workday tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long develop operational talent and succession plans takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your VP Operations or COO

What's the biggest bottleneck in develop operational talent and succession plans today — and would AI address the bottleneck or just speed up something that's already fast enough?

They're prioritizing which operational processes to automate

your process improvement or lean lead

If we automated the routine parts of develop operational talent and succession plans, what would the team do with the freed-up time?

They understand the workflow dependencies that AI tools need to respect

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.