How to become a data leader
When it comes to data, it pays to be leader of the pack
For the everyday company, data presents a unique opportunity. Data is something all businesses have, from the two-employee startup operated in a garage to the global enterprise monopolising markets. Learning how your company catches data, how it stores it, and most importantly, how it can use it can be key in creating unrivalled customer experiences and propelling your business ahead of the competition.
Here lies the problem. According to research conducted by Oracle, only 37% of marketing decision-makers state customer data is completely manageable. Marketing teams are being overwhelmed by the sheer volume of data they are tasked with processing. Opportunities are slipping through their fingers. The 37% chunk that are managing their data can be referred to as ‘data leaders’, and becoming one should be a business priority.
Spotting a data leader
Data leaders make the most out of their data, following the rules and squeezing out every last drop of insight possible. To become one, it helps being able to pick one out of a lineup which includes data ‘followers’ and ‘laggards’.
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The key characteristic that defines a data leader is the ability to produce meaningful insights from swathes of data. Data leaders deploy the most-up-to-date technology while having automated processes in place to create an efficient data pipeline that leaves no stone unturned. This all makes data more manageable, with Oracle’s research revealing that almost two-thirds of data leaders consider themselves completely on top of their data.
Technology not only helps in generating insights but is also crucial in order to ensure your data is securely managed. Taking accountability for security allows your marketing department to operate freely and with confidence, and goes some way to protecting reputations; there’s nothing like a security or compliance breach to discourage customers and clients from transacting and sharing details, with Oracle’s research revealing that over 90% of data leaders state data management impacts their reputation. A secure data management strategy boosts customer loyalty and cements brand value.
Of course, technology alone is never enough. The employees of a data leader will be educated as to their data responsibility, allowing them to be diligent in their work. As well as being equipped with the right technology, they will be taught how to properly use it. Lastly, when handling data the right ethics must be in place to ensure compliance with overarching regulations.
The steps towards a data leader
If your data team lacks the above characteristics, your company falls short of being deemed a data leader. Fortunately, there are clear steps you can take that lead from the very bottom to the very top.
Your data strategy should be built with automation at its heart. Setting course on your journey, it’s vital to move away from manual processes for extracting data insights, towards automated ones. A buyer’s group can assemble, consisting of decision-makers across the business, in order to identify a vendor that suits. Once integrated, your automated solution will dramatically reduce human error and increase processing efficiency, helping produce insight that you can trust in a fraction of the time.
But employees still have a crucial role to play. They must be educated, introduce data management best practices, and ensure these are followed by the entire marketing department by means of regular training. It’s up to department leaders to keep an eye on evolving data management requirements, and filter updates into refresher sessions. These measures will empower employees, providing them with the right mix of tools and information to have confidence when dealing with data, allowing them to make better-informed decisions that go some way in boosting the customer experience.
Attempting to forge a data strategy can at times feel like an endless marathon. The pace at which regulations and technology evolve is difficult to keep up with. So it pays to have both long and short term goals. Goals must, of course, be flexible, whilst being strict enough to measure progress. Long term strategies should be fixed on the horizon, and short-term strategies adjusted in order to arrive there in one piece. Perhaps the best place to start is at the bottom. Aim to tidy up the data you already have, strip duplicates and run due diligence.
With a foundation established, data can be confidently managed and analysed, and in time, the ladder climbed towards becoming a data leader.
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