The bets are in, the stakes are high: Business and IT leaders are invested in big data strategies.
With all their cards on the table, it’s no surprise they’re under pressure to make the most of their data strategy investments.
The only question remains: how? Even when embarking on new data and analytics projects, it’s still difficult to sift through a wealth of data in an intelligible and consistent way, especially with teams that may have a knowledge or skills gap.
When embarking on new data projects, these are the top five challenges we’re seeing business and IT leaders face (and continue reading for how to solve them):
Challenge #1: Lack of Alignment to Business Outcomes
The biggest challenge we see is that data and analytics projects are often seen as solely technology projects, making these projects disconnected from business objectives. When business leaders view data and analytics projects as more than just a technology improvement, they align them to business priorities. This ensures their data and analytics are set up to support the business goals, and that they can deliver real insights from their data.
Challenge #2: Too Many Data Silos
When data exists in many different formats and in lots of different locations, it’s not easy for business users to find and use that data. Without a proper way to catalogue and pull all the assets together in one place, you’re creating more and more redundancy across the organization.
Challenge #3: Fragmented Data
Imagine hundreds of people trying to communicate, all from different countries who speak different languages. That’s what today’s data is like. It’s in different formats and unorganized – it doesn’t speak the same language. And it leads to data inconsistencies and, eventually, a lack of trust in the insights derived from it. In fact, it’s estimated that less than 50% of structured data collected from IoT is actually used in decision-making.
Imagine if you had a universal language that they all 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 to your data.
Challenge #4: No Data-Driven Culture
Who’s in charge of ensuring your organization is a data-driven one? Today, that’s IT leaders. Yet, it’s not as simple as it sounds and most organizations lack the knowledge around building a data management strategy and the skills to execute it. Expertise, thought leadership, and experience is required to help companies push their data culture forward. It can’t be the responsibility of one department; rather, for organizations to truly leverage business insights, there must be enterprise-wide alignment on creating a data-driven culture.
Challenge #5: Skills and Knowledge Gap
While IT and business leaders want to invest in new data and analytics strategies and platforms, not enough organizations are actually evaluating if the team they have today is made up of the right skills and experience to be successful. This doesn’t mean replacing your existing team, but rather identifying skills gaps and bringing in expert opinions who can help fill those gaps in the short-term while teaching your existing in-house team to leverage new platforms.
These challenges all lie to missed opportunities and lost revenue. In fact, it’s estimated that companies that harness big data’s full power could increase their operating margins by up to 60%.
Solving These Challenges
These are the five biggest challenges we see organizations face as they embark on changing their cultures and embracing new data and analytics strategies. It’s no longer a question of if you’ll embrace a new data and analytics strategy, but when. And when that happens, you have to make sure you’re set up for success.
That’s what we do. At Gensquared, we look at data and analytics strategies as not just an IT or technology project but as a business project. We help you align your business on the core objectives you want to achieve and then how the data and insights play a part. We also help compliment your team’s existing skillset with our own experts too. All in an agile, timely manner. We call ourselves a Data-Team-as-a-Service: think of it as your data team on demand, ready to help you tackle your biggest data and analytics problems.
Stay tuned for the next blog in this series on what exactly a Data-Team-as-a-Service is, and why this approach has worked for so many of our clients.