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 Insights
The biggest challenge revolves around gaining insights from your data. The majority of data is unstructured or in different formats. This poses an increasing challenge for organizations to capture and analyze data in order to derive actionable insights. There are too many platforms, too many different tools, too many disparate systems that require manual intervention to get anything useful out of the data. Without quick, reliable and easy access to insights from their data, their ability to differentiate themselves from the competition is greatly reduced.
Challenge #2: Too Many Data Silos
Bridging the data silos – sharing the data with the rest of the business – is another common challenge most organizations are still grappling with. Business leaders want to enable cross-departmental collaboration and data integration. This collaboration and integration are often impeded by a lack of finding common consensus on departmental priorities, methodologies, or agendas.
Challenge #3: Fragmented Data
Historically, data was highly centralized, structured, and organized. But today’s data is uncentralized, unstructured, in different formats, and unorganized. This leads to data inconsistencies and eventually, a lack of trust in the numbers.
The data universe is growing exponentially every year, and along with it, the volume of data that most companies have makes them run the risk of never even leveraging all of it. In fact, it’s estimated that less than 50% of structured data collected from IoT is actually used in decision-making.
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.