• Sonia Johnson

3 Hurdles Businesses Should Overcome To Improve Data Analytics

We repeatedly see surveys that talk about the fact that most CIO’s and IT executives believe they are not prepared to make full use of the data flowing into and out of their organisations. Believing that they either lack the appropriate data and analytics capabilities, face cultural challenges or are working with outdated and costly data platforms. Here we identify three obstacles that businesses need to overcome to ensure they make the most of their data and analytics investments and get started on the right track.

While there is a wealth of data available to organisations, it is often the case that businesses can’t reap the full benefits of their analytics efforts unless their technology organisation is up to the challenge of managing the data that makes it possible. Unfortunately, organisations that know how to manage data as an asset and use it to drive innovation are the exception, not the rule. According to a 2021 survey highlighted in the Harvard Business Review, close to 7 out of 10 organisations are still struggling:

  • Only 29.2% of executives report achieving transformational business outcomes

  • A mere 30% report having developed a well-articulated data strategy

  • More concerning however is that “data-driven abilities” are reported to be on the decline

Gartner have shared at this year’s Data & Analytics Summit that data analytics leaders have identified their top three priorities being - data quality (51%), ROI from data and analytics investments (44%) and data sharing (43%). Given there is a consensus that there is work to be done to maximise value from investments in data and analytics, then what’s going on? Working with organisations to improve their data and analytics environments, BoomData typically see the following three obstacles within organisations that first need to be addressed:

1. The Data Divide Between IT & Business

Executives report in the Harvard Business survey for the fifth consecutive year that cultural challenges represent the biggest impediment around data initiatives, with 92.2% reporting that they continue to struggle with organisational alignment, business processes, change management, communication, people skill sets and resistance or lack of understanding to change.

It’s fair to say that IT may not always know where the value resides in data, while business users may not understand the intricacies of managing it. This can cause a disconnect that can have expensive consequences if the business (who own the data) and IT (who manage the data), make decisions without a solid understanding of each other’s perspective. Organisations can benefit by focusing their data initiatives on clearly identified high-impact business problems or use cases. By starting where there is a critical business need, executives can demonstrate value quickly through “quick wins” that help a company realise value, build credibility for their investments in data, and use this credibility to identify additional high-impact use cases to build business momentum.

2. Making Data Accessible & Useful

Companies must re-examine the way in which they think about data as a business asset of their organisation. Data flows like a river through any organisation. It must be managed from capture and production through its consumption and utilisation at many points along the way. Companies can often fall short by focusing solely on the back-end (how to manage, store and secure data), with the front-end (the user-interface) being a secondary thought. Value comes from putting data into the hands of business people who rely on it to make informed decisions to improve performance - this is where a lot of businesses stumble. Empowering users to access data, insights and business logic earlier and more intuitively will enable the move from static reporting to visualisation self-service and data self-sufficiency. The ability of business leaders to quickly use data from operational applications to make strategic decisions and deliver on strategic outcomes will rapidly be seen not just as a potential competitive differentiator, but also as a strategic imperative. The most progressive companies take this even further to look at data as an “ecosystem” opportunity, where insights arise from the combination of data emerging from interconnected data networks.

3. Relying On Old Processes & Technologies That No Longer Fit The Business

Often businesses can be saddled with legacy data environments, business processes, skill sets and traditional cultures that can be reluctant to change. While mainstream companies according to the report in Harvard Business Review appear to be confronted with greater challenges as demands increase, data volumes grow and companies seek to mature their data capabilities. With more people required to access data and make discoveries, a traditional data warehouse that secures and restricts access to only a few isn’t going to work. In addition, with the rapidly increasing complexity and amount of data, security and performance have become critical components for data analytics and have required businesses to re-look at old processes and technologies. For these, cloud-based infrastructure can work better than on-premise systems because they can be scaled up, provisioned on-demand and paid for based on usage. According to Gartner by 2023, 75% of all databases will be on a cloud platform. One such platform is Microsoft Azure, which offers a comprehensive and integrated data analytics and data management platform in the cloud, providing the ability to gather, store, process, analyse and visualise data of any variety, volume or velocity.

Whatever your challenges, the ones listed above are common barriers to deriving value from data and analytics investments. One imperative is to update old processes and create a tighter working relationship between IT and the business, by bringing the business closer to the development process. Agile development methods, which build applications incrementally with frequent input and review from the business, are an essential step. Data-driven business transformation is a long-term process that requires patience with investments in data governance, data literacy, programs that build awareness of the value and impact of data within an organisation. Businesses must show that they are in it for the long haul and not abandon efforts when results are not immediately forthcoming. Successful CIO’s will be those that move from a technologist’s view to one that allows a broader group of business users to access data, experiment with analytics and derive new insights that deliver meaningful value to the organisation.