Why Smarter Data Protection Is Now A Business Essential

When cyberattacks and their aftershocks make the evening news, data protection enters the spotlight. Take the recent attack on UK retailer Marks & Spencer, where online sales have only just been partially reintroduced, months later. The conversation quickly turned to how vulnerable data can be - and how even well-established, trusted organisations are at risk.

But the truth is, every CIO understands the importance of safeguarding data. Every IT leader worries how a cyberattack, system failure or natural disaster could damage their organisation. And every cyber security professional knows that as we rely more on digital infrastructure, our approach towards resilience needs to adapt and mature.

The big challenge is how to do that. How do we go beyond basic recovery strategies and begin integrating real-time visibility, anomaly detection and automation? So that as well as protecting data, it’s possible to recover more quickly and securely when the inevitable happens. How do we move towards more intelligent resilience: an approach that uses real-time data, predictive insights and automation to spot issues early, contain damage and recover faster?

Rethinking Data Protection

Traditionally, disaster recovery has been reactive: responding to a disruption after it has occurred, rather than preventing it or minimising its impact. With manual recovery and failover processes that rely on human intervention, getting back online can be slow and prone to errors. Plus limited testing can lead to unexpected issues when disaster strikes. All this, and more, means that downtime is often much longer than it needs to be. And as organisations like Marks & Spencer know, that can cost millions, hit share price and damage customer trust.

Rather than simply reacting to incidents, intelligent resilience starts well before operations are disrupted.

Teams taking this approach visualise risks and proactively plan recovery paths to minimise disruption and bring systems back online as quickly as possible. They use insights to detect threats early. And they prioritise compliance and data integrity so that data is recoverable, usable and secure, no matter what happens. 
By embracing this forward-thinking model, organisations are not just responding to incidents - they are actively preventing them.

What An Intelligent Resilience Strategy Looks Like

There are five steps that I would recommend to anyone considering an intelligent approach to resilience. These steps build on traditional best practices but add layers of visibility, automation and proactivity, so teams can prepare, respond and recover more effectively.

1.    Evaluate your current strategy 
Start by reviewing existing data protection and disaster recovery plans. Where are the gaps? Are you relying on legacy systems or manual processes that might slow things down during an incident? Do your current solutions cover all your SaaS workloads? Understanding your baseline is critical before making improvements.

2.    Leverage advanced dashboards 
The right dashboards can turn raw data into meaningful intelligence, helping you take early, informed action before small issues escalate into major outages. Real-time monitoring enables immediate action to mitigate risks before they become critical. 

Prioritise transparency: monitor backup status, identify gaps and gather insight into data integrity and compliance. Scan for irregularities in data patterns so that it is easier to identify potential threats like ransomware or data corruption. And plan how you will use that foresight to avoid disruption or recover more quickly.

3.    Automate recovery processes 
Automation also ensures consistency, so every recovery follows the same tested, validated steps, regardless of who is on duty or how serious the situation becomes. As well as offering greater protection against disruption and outages, introducing automation where you can also frees up the IT team to focus on more strategic priorities.

4.    Ensure governance & compliance 
Without transparent audit trails and constant compliance monitoring, organisations risk breaching regulations, losing customer trust and complicating recovery efforts. Taking an intelligent resilience approach to governance and automating where possible can reduce compliance risks, strengthen cybersecurity and ensure seamless, audit-ready recovery.

For example, automated data governance protocols can maintain security and regulatory compliance throughout the recovery process - removing the risk of human error at a highly pressured time. And monitoring and policy enforcement can help to protect sensitive data, ensuring it complies with legal and industry standards when it’s restored. 

5.    Test & adapt regularly 
Your resilience needs to evolve with your business and the threat landscape to make sure you stay ahead. Schedule frequent, non-disruptive tests to simulate failures and uncover weaknesses. Use findings to improve automation scripts, revise response protocols and train teams under realistic conditions.

The Path Forward

It’s time to rethink resilience: it’s more than protection, it’s also how quickly and effectively you can bring systems back online to minimise disruption.

By integrating advanced monitoring, anomaly detection and real-time visibility, disruptions are not just managed; they are mitigated before they happen. Let’s move resilience forward. 

Dan Middleton is VP for UK & Ireland at Keepit

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