As I tuned in to the final days of coverage of this year’s Commonwealth Games, I couldn’t help but think about data management.
Stay with me. I know it sounds strange, but this year’s Games were a lot like the situation that businesses face today.
With more than 70 countries taking part, the field was more competitive than ever. Tougher athletes swam harder and ran faster than ever and a handful of young competitors burst onto the scene to disrupt the veterans.
Gold went to those who constantly fine-tuned their skills. Standing atop the podium were the athletes who can react to changing conditions quickly, those with a strong support team and those who seek out timely and relevant information.
Businesses need to think like athletes. They need clarity on what they want to achieve, access to the right information at the right time, and the right skills to make use of it. They need flexible and supportive partnerships and to work within a mindset that values robust security, governance and compliance environments.
We are all heading into a new arena dominated by emerging technologies such as artificial intelligence/machine learning (AIML), robotic services, reality and wearable technologies. In this competitive environment, data determines the winners and losers.
The secret to being data fit
Success in today’s digital economy requires businesses to organise, structure and store data in a way that best supports their technology innovation initiatives. These initiatives can then be used to reduce costs and drive greater profitability, deeper customer engagement, and brand differentiation. I call this being ‘data fit.’
The key to being data fit is having one data source driving your solutions – a single source of truth.
But this is becoming increasingly difficult as data volumes increase. A 2015 study by Tech Research Asia found that Australian firms expected to see a 60 per cent increase in data growth in their organisation by 2017. Two years later, firms expected 103 per cent increase, with most of the data in an unstructured form.
Amidst this flood of data, businesses are struggling to integrate and manage data sources across multiple environments, enable more timely access to data and manage increasingly complex security and compliance requirements.
So how can businesses begin their data fitness journey?
The first step may be to change the way you think about data. Again, channel your inner athlete. Instead of fearing your opponent’s strengths, use them to differentiate your own skills.
Businesses that are succeeding in data management are already looking at ways to more formally recognise data as an asset for inclusion in their financial accounts. Instead of viewing data compliance as an impediment, they know good data governance has the potential to be a positive and strategic differentiator for their business.
Just like individual fitness levels, companies will excel in certain areas and struggle in others when it comes to being data fit. And as with any new fitness regime, the hardest part is getting started.
Here are a few questions to consider in the first three, six and 12 months.
Over the first three months
To get started, businesses should consider their data environment from the entire lifecycle perspective. Look at how data is collected, where it is used and for how long. Perform an audit of your current data sources and their relevance to your innovation initiatives and find out the absolute bare minimum amount of data your organisation needs to provide a service to customers.
Then consider what external data sources will you need to integrate into your solution, what data is ‘operationally required and what data your company retains or discards.
Make sure your organisation is cognizant of Australian, New Zealand and Asia Pacific data and privacy laws and determine your level of exposure to the new Australian mandatory data breach legislation and the EU GDPR regulations. Designate a person (or persons) within your organisation to be formally responsible for data governance and begin to put frameworks in place to address issues such as shared data, consent, transparency, and data location.
Next, consider your innovation technology plan and the impact your current data fitness will have on its success. Make sure you have metrics in place to assist in assessing what value is created from the data, so that you can track your progress moving forward.
By month six
Six months in, your data management capabilities should be more sophisticated and robust. Considerations at this point might include whether your policies are clear or heavily couched in legalese.
Even if your data is local, plan for global regulatory environments and use the most restrictive data requirements as your benchmark. Remember that privacy expectations, responsibilities and liabilities will extend from your organisation to your data partners as well. Query your cloud providers to understand their compliance stance and ensure there are no holes to plug.
At this time, it would be appropriate to make sure your organisation has determined how it will classify data for record storage purposes and address both the right to erase, and right to be forgotten requests from consumers, remembering that de-personalising data is not the same as destroying data.
And don’t forget your employees. They have data rights inside your organisation that must be considered as well, including what happens to their data if or when they leave the business.
By the end of the year
A year on from the start of your journey to become data fit, your business should treat data as a strategic asset and actively evaluating and maximising its value. Recognise your data on the company books, if appropriate, and ensure the metrics you are using to measure the value and contribution of data management to business outcomes are shared and understood across the business.
There is no endpoint to ensuring your data is fit for the competitive environment on the horizon. Data fitness requires perseverance, patience and the ability to recognise data as the lifeblood that powers your innovation technologies.
