# Master Data Steward Staffing Calculator

> Source: https://netray.co/tools/master-data-steward-staffing-calculator
> Publisher: Netray (netray.co), AI and integration engineering for ERP and manufacturing systems.
> Section: Free Tools

## Short answer

Convert monthly master data requests into the number of stewards you need, with rework, review time and utilization built in.

## Category

erp-operations

## Audience

- MDM lead
- Data governance manager
- ERP administrator
- Shared services manager

## Tool

**Kind:** calculator

**Inputs:**

#### New records per month

**Key:** creates

**Type:** number

**Default:** 900

**Min:** 0

**Step:** 50

**Unit:** records

**Help:** Items, vendors, customers, BOMs and routings combined.

#### Change requests per month

**Key:** changes

**Type:** number

**Default:** 1800

**Min:** 0

**Step:** 50

**Unit:** changes

#### Minutes to create one record

**Key:** create_min

**Type:** number

**Default:** 12

**Min:** 0

**Step:** 1

**Unit:** min

**Help:** Including looking up classification, units of measure and valuation setup.

#### Minutes to process one change

**Key:** change_min

**Type:** number

**Default:** 5

**Min:** 0

**Step:** 1

**Unit:** min

#### Review and approval minutes per request

**Key:** review_min

**Type:** number

**Default:** 3

**Min:** 0

**Step:** 0.5

**Unit:** min

**Help:** Second-person check or workflow approval time.

#### Rework rate

**Key:** rework_pct

**Type:** slider

**Default:** 15

**Min:** 0

**Max:** 60

**Step:** 1

**Unit:** %

**Help:** Requests returned for missing or wrong data.

#### Productive hours per steward per day

**Key:** prod_hours

**Type:** number

**Default:** 6

**Min:** 1

**Max:** 8

**Step:** 0.5

**Unit:** hours

#### Working days per month

**Key:** days

**Type:** number

**Default:** 21

**Min:** 1

**Max:** 31

**Step:** 1

**Unit:** days

**Outputs:**

#### Processing hours per month

**Key:** touch_hours

**Expr:** (creates * create_min + changes * change_min) / 60 * (1 + rework_pct / 100)

**Format:** hours

#### Review hours per month

**Key:** review_hours

**Expr:** (creates + changes) * review_min / 60

**Format:** hours

#### Total workload

**Key:** workload

**Expr:** touch_hours + review_hours

**Format:** hours

#### Capacity per steward

**Key:** capacity

**Expr:** prod_hours * days

**Format:** hours

#### Stewards required (FTE)

**Key:** fte

**Expr:** workload / capacity

**Format:** decimal

**Primary:** true

#### Whole stewards to hire

**Key:** headcount

**Expr:** ceil(fte)

**Format:** integer

**Primary:** true

#### Utilization at that headcount

**Key:** util

**Expr:** if(gt(headcount, 0), fte / headcount * 100, 0)

**Format:** percent

**Chart:**

#### Stewards required vs monthly new records

**Type:** line

**X:** creates

**From:** 100

**To:** 3000

**Steps:** 30

**Series:**

- fte

**Disclaimer:** Planning model only. Time per record varies widely by record type, so measure a week of real tickets before fixing headcount.

## Content

**Intro:** Master data teams are usually sized by gut feel until the request backlog grows. This calculator converts monthly create and change volumes into stewards required, including review time and rework, so you can defend a headcount number or show how workflow automation shrinks it.

**Sections:**

#### How to use it

**Body:** Count requests from your ticketing or workflow system over a representative quarter, separating new records from changes, because creating a record usually takes two to three times longer than editing one. Enter the minutes from time sampling, not from policy. Review minutes cover the four-eyes check that many governance programs require. Rework is the share of requests bounced back for incomplete data; it inflates processing time and is the quickest lever to pull. Productive hours should be well below eight, because meetings, queries and system waits eat the day.

#### The method

**Body:** Processing hours are the sum of create and change minutes, converted to hours and multiplied by one plus the rework rate. Review hours apply to every request. Total workload divided by a steward's monthly capacity gives full-time equivalents, and the whole number is the rounded-up headcount. The utilization line tells you how loaded that headcount will be, and a result above roughly 85 percent leaves no room for peaks such as product launches or acquisitions. The chart shows the workload line is linear in volume, so a volume spike translates directly into headcount.

**Bullets:**

- Workload = (creates x create min + changes x change min) / 60 x (1 + rework)
- Review = (creates + changes) x review min / 60
- FTE = workload / (productive hours x days)

#### Reading the result and avoiding mistakes

**Body:** If the answer is 4.3 FTE, hiring four stewards means about 108 percent utilization, so either hire five, cut rework, or remove low-value requests. Common mistakes include ignoring bulk loads, which are better handled as projects, forgetting that vendor and customer records need compliance checks that lengthen handling time, and treating all record types as equal. Run the calculator once per record domain if the skills differ. Reducing rework from 15 percent to 5 percent through mandatory fields and validation rules often saves more capacity than any hire.

**Cta:** If requests mostly wait on data lookups and validation, an AI assistant that drafts the record from the request and flags gaps can cut handling time. Netray builds that over your ERP with a steward approving each write.

**Faq:**

#### What productive hours per day should I use?

**Answer:** Five to six hours is a common planning figure for transactional data work once meetings, email, training and system delays are removed. Using eight hours systematically understates headcount and produces backlogs.

#### Should I include data cleanup projects?

**Answer:** No, keep project work separate. Steward capacity here covers steady-state requests. Cleanup campaigns need their own effort estimate and often temporary resources rather than permanent hires.

#### How do I measure create and change minutes?

**Answer:** Time a sample of at least 30 real requests per record type, including lookups and corrections, using timestamps in the workflow tool where available. Averages from a single experienced person understate what a new steward will take.

#### Does centralizing stewards reduce headcount?

**Answer:** Often yes, because specialization and consistent rules cut rework and handling time, but the gain depends on how fragmented your current process is. Compare the output here before and after reducing the rework rate.

## Search terms

master data team size calculator, how many data stewards do we need, master data management staffing, data steward workload, mdm team sizing, master data request volume fte, shared services master data fte

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