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The 5 Data Strategy Questions Everyone is Asking

With the rise of talk around Data, many have been encountering some real sticking points when developing their data strategy. Data experts & Camelot members Marisa Murton and Paul Rich have combined forces to answer your questions and guide you on your way to data clarity.

Data is a hot topic right now, and for most of us, one that’s a bit too hot to handle. 

More and more people are realising just how invaluable data is, and with that, wondering how they can squeeze the most value out of it. As more understand how priceless data really is, and as the sheer volume of accessible data increases, so do the questions, making data strategy an even hotter topic than data itself. 

So, here are the answers to the five data strategy questions on everyone’s lips.

1. What is data strategy? 

First and foremost, what is it? 

Data strategy is all about developing a clear understanding of the data that an organisation has and then identifying and defining the ways that this data can help the business achieve its goals. 

Once the data is understood, a strategy can be developed, which will work like a roadmap, carving a pathway to success. 

2. How important is data strategy and do I really need it?

It’s a tech world out there and it’s ever growing (and it doesn’t seem to be stopping anytime soon). In a space where we can ask Alexa to turn on the lights and get robots to do the hoovering, being left behind is the last thing anyone wants, especially organisations.

To keep up with this brave new world, data strategy is going to be the key. As businesses grow and margins are squeezed, companies must increasingly look at their data to give them insights invisible to the naked eye and to also highlight opportunities to act in those game-changing ways.

Unsurprisingly, data will lie at the heart of such forward thinking. As things stand, data is the ‘fuel’ by which a company runs, providing the information it requires to monitor, manage and deliver products and services. That being considered, it makes a lot of sense to think carefully about how we’re using the data available to us.

3. How do I get the maximum value for my data?

Capture it for a start (and ideally in a validated format)! Capture, categorise, consolidate and commercialise.

You can also be mindful of key fields, which allow you to join data sets together (client numbers, postcodes, etc). Try to make them as clean as possible and store all data assets in a single secure environment like the Cloud. 

Think outcomes: what outcomes do you want to improve, and make sure you capture those outcomes so that they can be used to identify trends and create models for the future.

And, more importantly than capturing it, make an effort to truly understand what you want to achieve through the use of data in a business. It could be used to improve key business measures like sales and routes to market, or to have better control and governance standards.

Fundamentally, however, data is everywhere in a business; only by understanding the true value of this data will a company properly realise best outcomes for its use.

4. What will need to change?

That absolutely depends on where the organisation is on its journey. A number of areas could be in need of a rethink – it could be the culture of the company, it could be IT, it could be ways of working.

Ultimately, of course, change isn’t something that just happens overnight, quite often it is the ‘mindset’ of a company that dictates the change that is brought about. Often it comes from a place of challenge in a business – a recognition that business is in need of modernisation, to adopt a more digital approach.

All of this can only really come to fruition when we first acknowledge the necessity of gaining a deeper, more intimate understanding of data, which organisations can then utilise to spark the catalyst for change.

5. How can data strategy help?

When data strategy is clearly defined and monitored, companies can execute their business plans faster, more efficiently and effectively, and with a lot more confidence!

The areas in which data strategy can be of value to companies will, as was previously highlighted, be dependent on where the organisation in question is on their data journey.

For instance, those with a good understanding of their data and performance can be further supported with the introduction of predictive analytics, which utilise past performance to model outcomes. By making the most of this process, companies can create automatable rules and even drive efficiencies.

Wherever a company is on their data journey, we can offer impartial advice based on our real experiences.

If you would like to know more about Data Strategy as a Service (DSaaS) please get in touch with either Paul Rich or Marisa Murton.

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