In this day and age, we don’t have to sell anyone on the value of data – companies know they have more data than ever before.
The challenge today is, how do we use the data in a meaningful way?
That’s why we talk about, not just conducting data and analytics projects, but actually building a data-driven culture.
4 of The Biggest Roadblocks When Building a Data-Driven Culture
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Oftentimes, when companies want to enable their staff to have access to information and data, they do so by putting a lot of technical people and resources as the middlemen.
The challenge? That’s not solving the root issue.
Building a data-driven culture means everyone in your organization, especially non-technical people, need to have access to data, in a way that doesn’t require them to go through a middleman or suddenly become technical savants.
Having a data-driven culture means you ensure that the average, non-technical person has access to the data they need to make decisions, and knows how to apply and interpret that data.
That’s where data governance becomes really important.
2. Change Management
The second roadblock we see to building a data-driven culture is change management.
It’s not necessarily a skills gap but rather a knowledge gap. Leaders want to be more data-driven but don’t know how to drive this change.
The third roadblock is the tools, and who gets to use them.
Implementing a new tool does not create a data-driven culture, but using tools for the right reasons can automate the process of getting the right data to the right people.
Because the minute somebody has to involve IT in figuring out how to access the data, then a question is asked:
How much time and effort is that going to take and how much of a delay will that impose on my ability to make a decision that’s critical to the business?
If you want to be agile, then you need to access your data to make real-time decisions.
If you need to make a decision an hour before a big board meeting, you don’t have the luxury of waiting a week for data.
Many customers we deal with are very focused on technology, such as a particular data project they want to complete. For example, Move to the cloud by X date.
Oftentimes, they hire or resource the technical staff to build things. But doing so in a silo means there’s no proper tie-in to the business value side of it.
So that’s the biggest failure. They build stuff that people don’t want to use, can’t use, or are geared towards a very small population who can use it.
Instead of simply building a new data platform or migrating to the cloud, you need to think about building data and analytics projects in a way that is:
- Flexible enough to deal with the complex needs of end-users
- Agile enough to address changes down the line
- Strongly correlated to your business objectives.
That’s part of the value we bring to the table: unlike consultants, who complete the technical work and leave, Gensquared focuses on the big picture of what your business wants to accomplish and only then which tools you need to do it.
That leads us to the next roadblock: which is a lack of trust.
When being data-driven is solely the responsibility of one department, this often diminishes the value that the technology platform can provide because there is a lack of trust in other departments.
This is why it’s crucial that the business and stakeholders are involved throughout the process so everyone is aligned on a common vision.
Imagine if you had a universal language that all stakeholders understood? Where you bring all data into a common framework to ensure consistency, integrity and validity of your data output.
That’s what normalizing and integrating data does – only then can you establish trust and integrity with your data.
Having a data-driven culture means you ensure that the average, non-technical person has access to the data they need to make decisions, and knows how to apply and interpret that data. #datadrivenculture Click To Tweet
Helping You Build a Data-Driven Culture
Our Data Team as a Service approach helps you solve these roadblocks and helps you truly build a data-driven culture.
Focus on your Business Goals
By focusing on your business goals first, and your technology needs second, Gensquared can sure that the technology project supports and drives your goals and objectives.
We don’t put technology in place to have the latest and greatest.
We take a business-first approach that ensures everyone is aligned on the business outcomes, so all departments have trust in the new process.
Finding your Internal Champion
Change management is one of the hardest challenges to tackle, which is why we work with you so you can see the value first.
This makes it easier to champion this new approach.
We do this by building you an MVP. The goal of an MVP is to drive awareness and get people exposed to what’s possible. We get you data very quickly, that suits your needs, that solves the problems you have in front of you.
That is the biggest, single most real way to get buy-in because now your business units recognize the value.
Include the Right Stakeholders
There’s often a disconnect between IT/technology departments and the rest of the org.
By bringing all key stakeholders to the table upfront, we ensure alignment between all groups. Then, that means once the technology is in place, more departments are likely to use it, since they’ve been involved from the getgo.
Data Governance and Security
When you increase data accessibility, there’s always a risk for security concerns.
This is where our data governance processes come into place, which leads to reliable outputs and reports while keeping sensitive information safe for those who should not be accessing it.
Those are just a few of the ways we help set you up for success.
Stay tuned for the next blog in this series where we focus on the difference between an agile, business-centric approach vs. a waterfall, technology-centric approach – and why it matters for building your data-driven culture.
Learn More About Building a Data-Driven Culture with these Resources:
- Culture, Not Technology Makes You a Data-Driven Company
- How a “Data Team as a Service” Model Works
- 5 Challenges Leaders Face When Launching Data & Analytics Projects