1. Introduction and Scope
This policy is for employees, workers and contractors of the Prime Furniture Ltd (PFL).
When processing personal data (defined below), Art 25 of the General Data Protection Regulation
(“GDPR”) obliges Prime Furniture to (taking into consideration the nature of the processing, risks to
individuals and costs etc,) implement appropriate technical and organisational measures, such as
pseudonymisation, into such processing activities in order to meet the requirements of GDPR
(including the processing principles) and protect the rights of the data subjects concerned. What are
‘appropriate measures’ may well change from one processing activity to the other and it is important that such measures are given consideration at the start of, and throughout, the life-cycle of the PFL’s processing of personal data. This obligation is referred to as ‘Privacy by Design’.
As a minimum, such measures must ensure that only personal data which are necessary for each
specific purpose of the processing are processed and that the personal data is not made available
to an indefinite amount of individuals without the data subject’s involvement (“Privacy by Default”).
This Policy provides guidance on the PFL’s approach to ensuring that it embeds privacy by
design and privacy by default across the PFL’s operations.
In the event the ICO finds that the PFL has not met its obligations in relation to Privacy by
Design and Default, the Information Commissioner’s Office could potentially impose a monetary
penalty of the higher of 2% of the PFL’s annual turnover or €10M. It is therefore important
that all staff understand and implement this Policy. If you have any questions, please contact the
PFL’s Governance Team in at email@example.com .
The following definitions apply to this Policy:
Personal Data: means any information relating to an identified or identifiable natural person (‘data
subject’); an identifiable natural person is one who can be identified, directly or indirectly, in
particular by reference to an identifier such as a name, an identification number, location data, an
online identifier or to one or more factors specific to the physical, physiological, genetic, mental,
economic, cultural or social identity of that natural person.
Special Category of Personal Data: means personal data revealing racial or ethnic origin,
political opinions, religious or philosophical beliefs, or trade union membership, and the processing
of genetic data, biometric data for the purpose of uniquely identifying a natural person, data
concerning health or data concerning a natural person’s sex life or sexual orientation.
Criminal Conviction Data: The rules for special category personal data do not apply to
information about criminal allegations, proceedings or convictions. Instead, there are separate
safeguards for personal data relating to criminal convictions and offences, or related security
measures. In order to process criminal conviction data we must either:
the additional safeguards set out in that Act.
For the purpose of this policy, when we are referring to ‘personal data’, we are referring to Personal
Data and Special Categories of Personal Data collectively.
Data Protection Impact Assessment (DPIA): an assessment of the impact of the envisaged
processing operations on the protection of personal data as referred to under Art 35 of GDPR;
as an Appendix to this Policy.
Where law or regulatory policy has changed since this Policy was written, those changes shall take
precedence and this Policy will be interpreted in the light of changes.
This Policy should be considered in conjunction with the guidance and forms for undertaking a DPIA,
which are available on the PFL’s intranet page for Data Protection.
A Data Protection Impact Assessment (DPIA) should be carried out where there is a high risk to
individuals. This may be as part of the initial phase of a project or when an existing project is being
reviewed. The DPIA should assess the risks to privacy and apply mitigation.
The principles of ‘Privacy by Design’ can be summarised as:
1 Use proactive rather than reactive measures. Anticipate, identify and prevent
privacy invasive events before they happen.
2 Privacy should be the default position. Personal data must be automatically
protected in any system of business practice, with no action required by the
individual to protect their privacy
3 Privacy must be embedded and integrated into the design of systems and
4 All legitimate interests and objectives are accommodated in a positive-sum
manner. Both privacy and security are important, and no unnecessary trade-offs
need to be made to achieve both.
5 Security should be end-to-end throughout the entire lifecycle of the data. Data
should be securely retained as needed and destroyed when no longer needed.
6 Visibility and transparency are maintained. Stakeholders should be assured that
business practices and technologies are operating according to objectives and
subject to independent verification.
7 Respect user privacy by keeping the interests of the individual uppermost with
strong privacy defaults, appropriate notice and user friendly options.
The PFL’s aim is to implement appropriate technical and organisational measures which are
(a) to implement the Data Protection Principles in an effective manner, and
(b) to integrate into the processing of personal data the safeguards necessary for that purpose.
This Policy applies at the time of determining the means of processing, and at the time of actually
processing the personal data.
In doing so, the PFL will take into account the available technical and organisational measures,
the cost of implementation and the nature, scope, context and purposes of processing of personal
data, as well as the risks of varying likelihood and severity for rights and freedoms of individuals
presented by the processing of their personal data.
If it is considered that the processing presents a high risk to individuals, a DPIA must be carried
out in accordance with the PFL’s procedures found on the Data Protection intranet page.
The PFL’s aim is that appropriate technical and organisational measures will be applied to
ensure that, by default, only the personal data which is necessary for each specific purpose of
processing of personal data is used, in relation to:
(a) the amount of personal data collected;
(b) the extent of processing that personal data;
(c) the period of its storage; and
(d) its accessibility.
The PFL’s aim is that by default personal data should be restricted to those who have a
business need to know.
The PFL’s aim is that when considering a proposal for a particular type of processing of
personal data, the impact of this on the individuals affected should be considered, and that
appropriate technical and organisational measures should be put into place to ensure that:
(a) the Data Protection Principles are implemented; and
(b) any risks to individuals’ rights and freedoms are minimised.
Vigilance by staff should be exercised continually to ensure the security of PFL systems and
personal data, e.g. against attempts to trick individuals into revealing their log-in details; and to
avoid risks of personal data breaches arising from mobile devices and remote log-ins. Staff should
avoid downloading, working with or storing identifiable personal data wherever possible, and only
undertake these activities in compliance with appropriate PFL guidance and policies.
Anonymised or partly/reversibly anonymised data should be used wherever possible.
When buying systems/software which involve personal data, or considering transfers/sharing of
personal data including using the “cloud”, staff must evaluate the privacy and security of alternative
solutions and vendors/partners. The use of such systems/software should to the maximum extent
possible avoid personal data being involved or put at risk of a data breach. Personal data should
only be placed on systems, devices or software where this is compliant with PFL policies and
the legislation. The use, and duration of holding, of personal data should be minimised.
Reviews of, and improvements to, privacy should be undertaken regularly by staff in their areas of
work, documented, and privacy risks and precautions reviewed by staff regularly. Further
information is available on the PFL’s intranet.
Managers or staff should not purchase new systems or software without first reviewing their
proposed use in terms of a Data Protection Impact Assessment if the proposed use presents a high
risk to individuals, and the proposed purchase also requires to be checked first by Procurement and
by Information Services for contract terms, and for the uses of, and risks to, personal data.
For purchasing supplies/services, regardless of contract value, no managers or staff should
approve a contract with a supplier unless the terms have been checked by Procurement (or the
PFL’s Solicitors) for data protection compliance.
Non-exhaustive examples of techniques which may be used to achieve these aims include
undertaking PFL-required data protection training and refresher training modules; maintaining
awareness of data security and threats such as ‘phishing’ attacks and other scams; carefully
considering email recipients, and avoiding emails to multiple recipients wherever possible; avoiding
the storage of spreadsheets containing personal data (anonymise and delete after use) minimisation
of collecting, storing, using and transmitting personal data used; regular deletion of personal data
after completion of purpose of processing or retention period; full and irreversible anonymisation of
personal data; regular checks to ensure personal data accuracy; pseudonymisation; encryption e.g.
of spreadsheets and other documents; filing personal data in PFL drives rather than using
Outlook as a storage medium; ensuring transparency for data subjects by Privacy Notice; restricting
staff access to personal data to those with a need to know; .
Another potential technique which may be helpful, provided that the number of individuals in the
dataset is large enough, may be to generate a dataset composed entirely of identity-disguised or
‘fictional’ individuals which can retain the statistical properties of the original dataset.
Article 5: Principles relating to processing of personal data
1.Personal data shall be:
(a) processed lawfully, fairly and in a transparent manner in relation to the data subject
(‘lawfulness, fairness and transparency’);
(b) collected for specified, explicit and legitimate purposes and not further processed in a manner
that is incompatible with those purposes; further processing for archiving purposes in the public
interest, scientific or historical research purposes or statistical purposes shall, in accordance with
Article 89(1), not be considered to be incompatible with the initial purposes (‘purpose limitation’);
(c) adequate, relevant and limited to what is necessary in relation to the purposes for which they
are processed (‘data minimisation’);
(d) accurate and, where necessary, kept up to date; every reasonable step must be taken to
ensure that personal data that are inaccurate, having regard to the purposes for which they are
processed, are erased or rectified without delay (‘accuracy’);
(e) kept in a form which permits identification of data subjects for no longer than is necessary for
the purposes for which the personal data are processed; personal data may be stored for longer
periods insofar as the personal data will be processed solely for archiving purposes in the public
interest, scientific or historical research purposes or statistical purposes in accordance with Article
89(1) subject to implementation of the appropriate technical and organisational measures required
by this Regulation in order to safeguard the rights and freedoms of the data subject (‘storage
(f) processed in a manner that ensures appropriate security of the personal data, including
protection against unauthorised or unlawful processing and against accidental loss, destruction or
damage, using appropriate technical or organisational measures (‘integrity and confidentiality’).
2.The controller shall be responsible for, and be able to demonstrate compliance with, paragraph 1