At a glance
A European logistics company relied on cloud services, business applications, warehouse technology, mobile devices and external suppliers to manage deliveries across several countries.
Its security team collected information from vulnerability scanners, endpoint protection, cloud-security tools, supplier assessments, audit reports and the central risk register. Each source provided useful information, but the records changed at different speeds and were maintained by different teams.
A system could be updated or retired without the change appearing in the risk register. A newly discovered vulnerability might be added to a technical queue without being connected to the affected business service. A security control could fail while still being shown as effective in a management report.
The company had enough data. The difficulty was keeping the relationships between that data accurate and current.
The security team needed to answer practical questions:
- ?Which critical systems had new vulnerabilities or security alerts?
- ?Had changes to assets or suppliers altered existing cyber risks?
- ?Which controls were operating as expected, and which required attention?
- ?Were risk owners being informed when important information changed?
- ?Which overdue actions required escalation?
- ?Could repeated manual updates be reduced without weakening human oversight?
- ?How could management receive a current view without waiting for the next reporting cycle?
We helped the client connect selected security and business data sources through controlled automation. Changes to important assets, vulnerabilities, controls, suppliers and remediation actions could update the relevant cyber-risk records or trigger a review.
Automation did not decide whether the company should accept a risk. It collected changes, applied agreed rules, highlighted inconsistencies and directed significant issues to the appropriate owner.
About the client
This case study presents a representative and anonymised client scenario. The company profile, quotation and results are realistic examples created for this scenario.
The challenge
The company’s cyber-risk information was distributed across several systems.
The vulnerability-management platform contained technical findings. The asset inventory provided information about servers, endpoints and applications. Procurement maintained supplier records. Business continuity documentation identified important services. The risk team maintained the central risk register, while remediation actions were tracked in service-management tools and spreadsheets.
These sources were useful individually, but they did not remain aligned automatically.
When an application owner changed, the risk record was not always updated. When a supplier began supporting another critical service, the new dependency could remain hidden. When an asset was decommissioned, open findings sometimes remained associated with it. Other systems appeared under different names in different tools.
The team carried out manual comparisons before quarterly reporting. This work took time and still provided only a view of the information at a particular moment.
The main problems were:
The client needed automation, but it did not want to automate decisions that required professional judgement or formal risk acceptance.
What the client wanted to achieve
The project had six main goals:
Connect reliable security, asset, supplier and business data sources.
Keep important relationships between risks, assets, controls and owners current.
Use automation to identify significant changes and trigger timely reviews.
Reduce repetitive manual updates and duplicate records.
Preserve human approval for risk evaluation, exceptions and acceptance.
Give management a more current and traceable view of cyber risk.
What we did
We identified the information that needed to remain current
We began by reviewing the decisions the security team made regularly and the information required to support them.
Together with security, IT, procurement, business continuity and selected business owners, we identified the most important information:
- ✓critical business services;
- ✓supporting applications and infrastructure;
- ✓technical and business owners;
- ✓data sensitivity and operational criticality;
- ✓internet exposure and remote access;
- ✓active vulnerabilities and security alerts;
- ✓relevant security controls and evidence;
- ✓suppliers supporting critical services;
- ✓open remediation actions and exceptions;
- ✓review dates, approvals and escalation status.
We did not automate every available data field. We focused on information that could change a risk decision or require action.
We agreed on authoritative data sources
Automation could not resolve poor data simply by moving it more quickly.
For each type of information, the client agreed which source should be treated as authoritative. The asset-management platform remained the primary source for technical assets. Procurement owned supplier information. Business continuity records provided the agreed list of critical services. The identity platform supplied ownership and access information where appropriate.
We also defined what should happen when sources disagreed.
The process could:
- ✓accept a value from the authoritative source;
- ✓flag the inconsistency for review;
- ✓retain both values until an owner resolved the difference;
- ✓prevent an automated update if the source lacked sufficient quality;
- ✓record the source, time and reason for every accepted change.
This prevented the automation from overwriting useful information with incomplete or unreliable data.
We connected assets with business services and risks
The client needed more than automated data transfers. It needed the relationships between the records to remain visible.
We created links between:
- ✓business services and supporting applications;
- ✓applications and infrastructure;
- ✓assets and technical findings;
- ✓assets and responsible owners;
- ✓suppliers and the services they supported;
- ✓identified risks and the controls intended to reduce them;
- ✓controls and the evidence showing whether they were operating;
- ✓risks and their open remediation actions, exceptions and review dates.
Alternative names and identifiers were retained so that records from different tools could be matched without losing their original reference.
We defined the changes that should trigger action
Not every technical update required a risk review. The client needed rules that distinguished ordinary activity from a meaningful change.
A review could be triggered when:
- ✓a critical asset gained internet exposure;
- ✓a high-priority vulnerability affected an important service;
- ✓known exploitation activity increased the urgency of an existing finding;
- ✓an important security control failed or lost current evidence;
- ✓a supplier began supporting an additional critical process;
- ✓an accountable owner left the role or could no longer be identified;
- ✓a remediation deadline or exception review date passed;
- ✓an asset changed function, location or criticality;
- ✓an incident affected a system connected with an existing risk;
- ✓several lower-level changes combined to increase the overall exposure.
The rules were documented and reviewed by the people responsible for the associated risks.
We automated routine updates and notifications
Where the source information was sufficiently reliable, routine updates could be processed automatically.
Automation was used to:
- ✓update selected asset attributes;
- ✓add new vulnerability information to the relevant asset record;
- ✓notify owners when a material change occurred;
- ✓open a review task when agreed criteria were met;
- ✓identify missing owners, expired evidence and overdue actions;
- ✓combine duplicate records where matching confidence was high;
- ✓send reminders before exception and review dates expired;
- ✓update dashboards after an approved change.
Every automated update included the source, date and reason. Where the process was uncertain, it created a review task instead of changing the risk record automatically.
We kept human judgement in the decision process
Automation supported the process but did not replace accountable decision-makers.
The following actions always required human review:
- ✓changing the formal level of a significant risk;
- ✓accepting remaining risk;
- ✓approving a remediation exception;
- ✓changing the business criticality of an important service;
- ✓deciding that a control reduced the risk sufficiently;
- ✓closing a significant risk or remediation action;
- ✓escalating an issue to senior management.
The responsible person received the relevant context, source information and recommended next step. The final decision, reason and date were recorded.
We introduced exception handling and quality checks
The automation needed a safe route for unusual or incomplete information.
An exception was created when:
- ✓two authoritative sources appeared to conflict;
- ✓an asset could not be matched confidently;
- ✓an owner could not be identified;
- ✓a required field was missing;
- ✓an integration failed or stopped providing information;
- ✓the number of changes exceeded an agreed threshold;
- ✓a proposed update would materially change a significant risk.
Regular quality checks reviewed unmatched records, failed updates, duplicate entries, missing owners and changes waiting for approval. This ensured that automation did not hide data-quality problems.
We improved reporting and escalation
The new reporting distinguished between ordinary activity and information requiring attention.
Management reporting focused on:
- ✓significant cyber risks that had changed;
- ✓critical services with new or increased exposure;
- ✓failed or unverified security controls;
- ✓overdue high-priority actions;
- ✓expired exceptions and missing approvals;
- ✓supplier changes affecting critical services;
- ✓records without accountable owners;
- ✓data-quality issues that could affect risk decisions;
- ✓decisions requiring management support.
Security teams could inspect the detailed source records, while management received a shorter explanation of what had changed and why it mattered.
What we delivered
The client received:
- ✓a prioritised map of cyber-risk information sources;
- ✓agreed authoritative sources and data-ownership rules;
- ✓a connected model covering services, assets, risks, controls, suppliers and owners;
- ✓automated updates for selected, reliable data fields;
- ✓change triggers and review rules;
- ✓automated owner notifications and task creation;
- ✓human-approval points for material risk decisions;
- ✓exception handling and data-quality controls;
- ✓escalation criteria and management dashboards;
- ✓operating guidance for maintaining and reviewing the automation.
The project did not automate the entire cyber-risk process. It automated repeatable activities while preserving human judgement where context and accountability were required.
The results
Within ten months, the company:
These results belong to the representative scenario created for this case study.
What changed for the client
What we learned
Client comment
“Before the project, our team spent a great deal of time comparing separate reports and checking whether risk records were still accurate. Automation now brings important changes to our attention much earlier. We still make the decisions, but we make them using information that is more current and easier to trace.”
This quotation was created for the representative scenario.
Conclusion
The company did not automate cyber-risk management to remove people from the process. It automated the repetitive work that prevented those people from concentrating on the most important decisions.
Connecting security findings with assets, business services, controls, suppliers and owners created a more current view of cyber risk. Agreed rules highlighted meaningful changes, while exceptions and material decisions were directed to accountable people.
The security team spent less time copying information and reconciling records. Risk owners received earlier notification of changes affecting their areas. Management gained a clearer view of current exposure, overdue actions and decisions requiring support.
Most importantly, automation strengthened the cyber-risk process without replacing judgement, accountability or formal approval.
Are you facing a similar problem?
Cyber-risk information changes constantly. Manual updates can leave risk registers, ownership records and management reports behind the operational reality of the business.
Cybersecurity Analytics can help you:
- ✓identify the cyber-risk information that needs to remain current;
- ✓connect assets, vulnerabilities, controls, suppliers and business services;
- ✓define reliable and authoritative data sources;
- ✓automate routine updates and owner notifications;
- ✓introduce change triggers and review rules;
- ✓retain human approval for important risk decisions;
- ✓improve data quality, traceability and escalation;
- ✓provide management with a more current view of cyber risk.
