Five Common Mistakes to Avoid when Implementing your Data Strategy

A movie character once said: “I cannot make bricks without clay.” This is the same mindset every marketing company should adopt in today’s data-driven world. At the same time, companies time and again make sweeping declarations to make data a priority, only to fall into traps that render these efforts unsuccessful. Here are the top five mistakes you should not commit:

A movie character once said: “I cannot make bricks without clay.” This is the same mindset every marketing company should adopt in today’s data-driven world. At the same time, companies time and again make sweeping declarations to make data a priority, only to fall into traps that render these efforts unsuccessful. Here are the top five mistakes you should not commit:

  • Being too attached to the current business processes. A change in data strategy has a lot of growing pains, but this is the biggest one. Managers, seemingly threatened by the changes in processes and operations that new strategies bring, adopt a bunker mentality by refusing to participate in the change process. To mitigate this, executives should emphasize that while changes to the current processes will have a temporary impact to the day-to-day operations, all the changes should be made towards improving existing processes and making employees’ lives easier.Being afraid to adapt. This is related to the first one. Leaders should encourage employees to learn new skills, especially those in operations, who may only have one skillset. This will allow employees to feel empowered rather than feel trapped in a hamster wheel. If employees are encouraged to learn new skills, they will be more responsive to change.
  • Being afraid to invest in technology. Companies make a lot of fuss about investing in data, yet when they evaluate software and products to establish their data platform, the tend to overemphasize the high cost, rather than the potential long-term benefits. They then revert to hiring cheap labor that can only do a few – if none – of a product’s capabilities. Companies should embrace automation, democratization, and transparency trends in data and technologies if only to liberate their workforce from doing menial, repetitive tasks.
  • Investing in the wrong resources. You’ve decided to invest in technology. What next? You need to be discerning in selecting the right product. Go for products that provide returns on investment sooner, rather than later. Starting off your data strategy by investing in analytics, data governance, and data quality tools is an ideal first step in gaining that advantage.
  • Failing to understand the value of data. In all, data will only be valuable to an organization if each employee understands how to harness it. It’s not enough that you have the tools, or hundreds of employees to work on them, if not everyone understands a) what data is being produced, b) how it’s being produced, c) how to responsibly handle them and d) how to use them to understand the company.

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