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How to go from data blindness to informed value


Johannesburg, 14 Apr 2021
Read time 5min 00sec
Chris Larkins, Business Unit Manager: Dell Enterprise, Tarsus.
Chris Larkins, Business Unit Manager: Dell Enterprise, Tarsus.

The Antarctic is a notoriously dangerous place. It presents many ways to harm humans, and even basic training in these conditions can save lives. One such exercise involves wearing a bucket on your head. The bucket simulates a heavy snowstorm – a whiteout – where you can't even see your hand in front of your face, also called being snow blind. Snow blindness can make walking even a few metres a perilous journey, so the bucket exercise is very important.

Today's company has a similar problem, but with data. Many are data blind, meaning they are so overwhelmed by data that they can't see a way forward. Though not as fatal as a sudden snowstorm, data blindness will eventually strip away competitiveness, demoralise employees and make the business an un-enticing prospect for new hires. Turning data into insight clears the air. But unlike wearing a bucket on your head, this outcome is daunting and challenging to pursue.

It's crucial to develop a technology foundation that supports a growing appreciation for data in the organisation. There are different places to start from, such as focusing on security and compliance. Yet in isolation, these approaches will only go so far, warns Chris Larkins, Tarsus' Dell Enterprise Business Unit Manager.

"Something such as compliance or security are important areas to focus on, but they aren't natural stepping stones. A few years ago, it became very popular to hire a chief data officer, with the idea that they would sort out all the data-related issues. But most of those guys became responsible for POPIA and such things, and much less with creating data insights. That happens because data shouldn't be one person's concern. It's something the entire business should be involved in."

Collaboration is key

No matter how ambitious, a single-focus data strategy will not go very far. It falls short of anticipated results and often becomes a cost conversation. The difference between successful and unsuccessful data projects, says Larkins, is collaboration: "Almost always, in the environments that aren't collaborative in nature, high-level discussions around data come back down to a budget and, typically, IT infrastructure budgets. Even if the business has bought into a data initiative, they typically don't have enough funding to do that. The entities that are more forward-looking understand the value of turning data into actionable insights. They collaborate in those board-level meetings and they can chip in from all sides."

Companies overlook that the people in charge of budgets or technology are often not the same people who stand to gain the most from data insights. Areas such as sales, marketing and risk management are often left out of the early conversations. Yet they are overwhelmed. A 2019 survey from Domo found that more than 80% of marketing leaders are struggling to stay ahead of technology and data. They are essentially data blind.

Roping their concerns into the conversation can greatly change attitudes around budget and what it will take to create success with data: "Creating a data estate is going to cost more money. Maybe it's a sacrifice across different sides of the business or a prioritisation exercise that needs to be done. But it does need to get done. So, companies have got to find the money somewhere if it's important enough, and collaboration between different groups elevates the importance and creates opportunities for everyone to chip in. This approach also helps establish the priorities for your plan."

Know what you have

Companies also often avoid discovering and auditing their data. This lapse can relate to budget or inconvenience and usually translates into leveraging cloud storage. Though the cloud is an excellent answer to managing many data demands, dumping everything in there for the sake of it is a self-defeating strategy. Instead, it's worth the time to discover what data you have and then decide on priorities that will lead to the outcomes collaborators are looking for.

"Once you've figured out the priorities, you should be asking: 'As an end-user, how do I find that data and how do I understand what it is?' There are many great ways to discover and audit data, often with tools vendors embed in their equipment."

After you have forged a plan through collaboration, you have identified your priorities and you have a good sense of what data is out there, you can focus on how to enable your most pressing concerns. This approach opens up new ways to interpret a data environment. For example, the data benefits down the line (such as giving marketing accurate customer profiles) can motivate the ROI for traditionally begrudged necessities such as compliance. Larkins points to PCI networks as an example: they are heavy on compliance but also feed into powerful data-powered capabilities for financial institutions.

You don't need to establish a data estate in one big bang approach. It's better to pick your battles. There is a risk that you could end up in a single-purpose project that doesn't translate into momentum elsewhere. But if you are armed with a well-designed plan reflecting your priorities, implement policies that will maintain the plan and audit your estate, then you are on the right track to find your way out of data blindness. 

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