Recently, I looked in my bank of vacation, sick and personal time and noticed that I have too much time sitting there. Then I talked to some friends and learned they have so much time stashed away, they’re likely to lose hours. But why is that? What causes us to not take our vacation time and sick days? I realized the reasons we don’t take time off are the same reasons data analytics projects are often derailed in major corporations and across the country.

The reason for success and failure is human nature — in both our personal lives and in business.

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CDW customers keep their data in a lot of different places: onsite, in the cloud (another person’s data center) or in an all-in-one data warehouse. Often, this data is siloed. But if an organization could harness the power of its data and become a data-driven organization, it would be able to grow and compete more effectively. The company could move mountains — or so the idea goes.

So Why Do Data Projects Fail?

The path to using data effectively is challenging, but not because organizations don’t have a desire to become data-driven. A few universal obstacles affect every organization, and a few subjective issues may depend on specific industries.

Universal reasons fall along these lines:

  • Most organizations have data compliance requirements. Even when data resides in a data warehouse, it still can’t be seen by everyone in a company. The organization can’t achieve the objective of having all of its users working off of one set of data and leveraging one standardized reporting set. Compliance requirements change depending on the industry and on the government; thus, multinational companies must operate under restrictions from multiple governments in multiple locations. Further, data efforts must overcome the human factor. No one wants to be the person who didn’t follow the compliance requirements.
  • Inside every organization is a power struggle. Ownership of data or infrastructure is tied to decision-making about data storage, access and who will determine the questions asked of the data. And that’s really an essential consideration. Data is only as good as the questions asked.
  • Assuming an organization overcomes the hurdles of compliance and politics, it must invest in a structure and a set of tools that will work across the organization. By the time the organization is ready to do that, a project may have new people working on it, with new goals, new ideas and new structures to be considered.

We face similar obstacles as we try to take time off of work. Inevitably, just when an IT professional wants to take time off, something changes. A resort increases its fees, inclement weather interrupts plans, and so on. I’ve talked with a lot of organizations across the U.S. that want to become data-driven; this has to start with the culture — and that’s where this conversation moves to something more subjective. Changing a static culture when it comes to data is challenging. It may seem like we take vacation; it may even seem like we know how to relax. But shifting from someone who lives life in harmony to someone who jumps back into work, well — it’s a huge leap.

Creating a Data-Driven Culture

I want to illustrate this point because a data-driven culture is really where analytics projects succeed or fail, and it’s something that executive leadership can absolutely create through a greater understanding.

Organizations don’t have a data-driven culture if:

  • They share reports top down
  • Coworkers can’t easily access numbers
  • They can’t interpret the numbers
  • They can’t leverage tools to understand their position

Data-driven cultures are created when coworkers have tools and access to data to help them understand how to positively impact the organization; when they are taught to ask intelligent questions of and with the data; and when politics cease to be an issue and they can use reports to share their impact and growth with other people — for the good of the organization.

It is a challenge to create a data-driven culture, much as it is a challenge to create a culture that encourages work-life balance. Both require a commitment on the part of the employer and the employee to work hard and meet each other’s needs. In companies and organizations that are successful with data culture, we typically see coworkers who are empowered to think for themselves. As you think about making the shift from static reporting and leveraging data banks to creating a data-driven culture, I hope you’ll consider this: The harmony we find in life can also be found in our data — and the challenges to find balance in life is reflected in our data analytics projects.

Good luck, and remember, we are here to help as you walk the path toward data synergy.

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