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## Chapter 1 — The role and the organisation

### Learning outcomes

You will (1) describe the professional course and its case; (2) outline the data a small charity holds; (3) set goals for a governance lead role.

### 1.1 The learner

Grace Mwangi is the new operations manager at Northbank Food Bank Network, a fictional charity running six food banks with about four hundred volunteers, four thousand donors and referral records for families who receive food parcels. Her trustees have asked her to take responsibility for data governance. She enrols on a six-month professional course at the fictional Kingsford Professional Academy, taught by Mr. Tomasz Nowak, which meets one evening a week and uses synthetic data for every exercise. Grace is eager to start.

### 1.2 Northbank's data

Grace lists the charity's data: donor names, addresses, emails and gift histories; volunteer contact details, availability and safeguarding checks; client referrals from social workers and doctors, including household size, reasons for need and sometimes health details; stock records of food received and distributed; and financial records. She notes that client referral data are the most sensitive, because they reveal hardship and sometimes health conditions, which the GDPR treats as special category data needing extra protection. She records each kind of data with the team that uses it.

### 1.3 Current state

Grace finds data spread across a donor database, spreadsheets kept by each food bank, paper referral forms in filing cabinets, a shared email inbox and volunteers' personal phones. Nobody has written rules on who may see referral data or how long it is kept. A trustee recently asked how many families were helped last year, and three food banks gave figures using different definitions of a family. Mr. Nowak notes that this is a typical starting point for a small organisation. Grace records this.

### 1.4 Goals

Grace sets goals for the course: know what data Northbank holds and where, agree who is responsible for each kind, protect client data properly, improve donor data for fundraising and report reliable figures to trustees. Mr. Nowak asks her to make each goal measurable, such as all six food banks using one definition of a household by the end of the course. She writes the goals in her course notebook and shares them with the chair of trustees. The chair welcomes the goals.

### Worked example

Grace, a new operations manager at Northbank, lists donor, volunteer, client, stock and financial data, finds scattered records and inconsistent family counts and sets measurable governance goals shared with the chair.

> **Synthetic case.** Northbank, Kingsford and all people are synthetic; the GDPR is real.

### Errors and limits

Treating a small organisation's data as too simple to govern leaves sensitive records unprotected.

### Exercises

- **EX001 — Course length.** How long is Grace's course? *Rubric:* 3 = six months;; 2 = partly correct;; 1 = wrong;; 0 = none.
- **EX002 — Most sensitive.** Which data are most sensitive at Northbank? *Rubric:* 3 = client referral data;; 2 = partly correct;; 1 = other;; 0 = none.
- **EX003 — Special category.** Why can referrals be special category data? *Rubric:* 3 = they sometimes contain health details;; 2 = partly correct;; 1 = vague;; 0 = none.
- **EX004 — Family figures.** What went wrong when trustees asked about families helped? *Rubric:* 3 = food banks used different definitions;; 2 = partly correct;; 1 = vague;; 0 = none.
- **EX005 — Measurable goal.** Give the course's example of a measurable goal. *Rubric:* 3 = all six food banks use one household definition;; 2 = partly correct;; 1 = vague;; 0 = none.

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## Worked answers

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**EX001.** Six months.

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**EX002.** Client referral data.

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**EX003.** They sometimes include health details.

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**EX004.** Food banks used different definitions of a family.

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**EX005.** All six food banks using one household definition.
