Boost your organisation’s reaction times

Today, it’s never been more important for organisations to react quickly or risk missing out on key opportunities. That’s thanks to the increasing prevalence of rapidly evolving and highly competitive markets across all sectors globally. This makes it business critical to be able to make the best possible decisions as fast as possible. And data analytics driven by artificial intelligence holds the key!

However, the reputation the discipline has gained for complexity, together with a general lack of knowledge and understanding, has created a fear factor deterring organisations from using data to its full potential. This presents a significant competitive advantage to those organisations that can break the fear barrier. Optimising the power of data analytics will open the door to deriving insights from your data in real time, both accelerating and improving decision making, and consequently transforming business reaction times.

I’m sure you can envisage many ways this would make a big difference to your organisation. But here’s one of the most recent growth areas: improving the customer experience. Catching the attention of customers has never been more important nor more difficult. With companies delivering a barrage of marketing messages on a daily basis, how can you stand out above the constant noise?

The answer lies in gathering as much data as possible by capturing customer actions and interactions to determine their specific needs, wants and overall behaviour. This can range from discovering product and service preferences to determining when they are in a buying frame of mind. That’s not just when they are open to receiving messages, but also how they want you to engage with them.

With real-time analytics, it’s possible to build detailed customer profiles quickly and accurately, and react to them almost immediately. Essentially changing the customer experience game with exceptional personalisation by always reaching your market at the right time, in the right place, in the right way.

Preparing for success

If you’re thinking: “Sounds great! But where do I start?”, read on! Kicking the process off is relatively simple. In fact, it should be a piece of cake if you understand your business, your market and your key objectives, which should guide every decision you make.

Think about your key goals and whether getting real-time insight from your data could help to achieve them. With relevant goals set, it’s time to determine key performance indicators and metrics to establish firmly what success looks like and measure your progress towards it. This is vital to keep you on track, as data strategies can be adjusted if necessary.

It’s also key to establish your return on investment. Data projects can be expensive, so you need to make sure they are financially viable. Ideally, preparing thoroughly in this way should ensure they are.

Once you’re established a clear direction for your data project – your North Star – it’s time to dive into the details. Take the following factors into account, and you will significantly increase the chances of success in terms of meeting your goals and justifying your investment.

Depending on the technology and data skill levels you and your team possess, you may well need help ticking some or all of these boxes. So, don’t panic. Expert help is out there, and it’s worth tapping into to secure the expertise you need to get everything in place for a successful data project.

Anyway, on to those key success factors:

Architecture

Identify what you need to change to ensure your system architecture is equipped with the processing power to handle your data project. What technology and tooling do you need to optimise data throughput and minimise latency? If you’re not there already, should you migrate to the cloud?

Data

Make sure you gain a thorough understanding of the structure, composition, behaviour and volumes of your data sources. This is crucial, because it can have a significant impact on the cost of the infrastructure and data services.

Processes

Carefully plan the data lifecycle. Establish how you will ingest the necessary data, how you will transform it so that it can be integrated with other sources, and how you are going to consume it.

People

Investigate what extra skills you will require to prepare, launch and run your data project successfully. Do you have the right technology team now? Do you have the right management and oversight resource in place to support the project? Then identify where to get the talent you need.

Prioritisation

Establish an order for the various use cases you are working towards. Start small through pilot testing and iterative development from what you’ve learned from the test.

Data governance and quality controls

It’s important to set up all the required compliance policies, plus objectives and key results (OKRs) to define measurable goals and track their outcome. This should be driven by the KPIs and metrics set in our first step.

Operational efficiency

Plan regular sessions to track and monitor your data process, your KPIs, success metrics and OKRs.

And finally, foster a data-driven culture by sharing progress, achievements, solutions, data artefacts, and promoting a space for cross collaboration.

Staying on track and always improving

With the planning over, it’s time to launch your data project. But before you do, you need to put monitoring processes in place that ensure it not only stays on track, but also learns as it progresses to drive continual improvement. These include:

Real-time monitoring

Deploy tools that constantly assess your system's performance, latency and uptime, with this information immediately accessible by key people in an intuitive format. This enables you to respond to any issues immediately or even before they happen, and also spot ways to improve processes.

Performance metrics

This information should also be used to gauge performance against your KPIs so you’re always aware how your data project is measuring up. This means you can quickly identify whether you’re not on track and, if necessary, consider solutions to regain your momentum.

Constant communication

It’s also vital to stay in touch with everyone involved, from your team to suppliers. Creating a continuous feedback loop through regular meetings keeps all parties up to date with progress, fully exploits the knowledge base of the team you’ve built, and avoids any sudden nasty surprises.

A data project shouldn’t be a one off.

You should be continually looking at how your growing amounts of data can help improve your performance.

Establishing the right architecture, then planning and monitoring each project as described above will drive the agility, adaptability and constant improvement you need to maximise the chances of success each time – and optimise the value of your data.

This will not only keep you moving forward, but also help future-proof your organisation.

Put data analytics to work across your organisation. Talk to our data team today!

Key takeaways

• The rise of digital technology continues to accelerate the amount of data organisations create, capture, copy and consume globally. This provides a valuable business resource, containing insight that can help keep organisations at the forefront of their markets, yet much of it remains untapped.
• Real-time data analytics, driven by artificial intelligence (AI), holds the key to unlocking organisations’ data potential. Managed in the right way, it rapidly analyses data, turning it into key actionable insight that enables faster, better, more informed decision making to transform operations, business planning and the customer experience.
• However, a lack of knowledge and understanding of data analytics, along with its reputation for complexity, is creating a fear factor that’s deterring organisations from realising its full potential.
• Taking the right approach through expert guidance can help put the required building blocks and processes in place to reduce complexity and develop a data analytics platform tailored to key needs and objectives. Finding the right partner with the necessary technical expertise and experience can remove a major burden off the shoulders of in-house IT teams.