Analytics Projects: 6 Common Reasons They Fail
Published
March 24, 2023
Why do so many analytics projects fail?
Data continues to be created and consumed at an increasingly stunning pace year over year. Predictions from global data experts show that humans will produce and consume about 118 zettabytes of data by the end of 2023.1
Soon, data itself will become a primary product for nearly every business, and data analytics will form the core of every company’s business model. Nearly every product on the market will be forced down one of two paths, becoming either “smart” (i.e., analytics- and data-driven) or obsolete.2
So, how do companies compete in a world where data becomes the primary product?
Most companies don’t know where, or how, to start. And so, they start to do ‘things’ and they fall into a spiral of complexity, and instead of removing complexity with data, the data adds more complexity.
Analytics project complexity often leads to costly failure.
85% |
of big data projects fail*
87%
of data science projects never make it to production**
20%
of analytics insights will deliver business outcomes*
So, what are the top factors causing this complexity and causing analytics projects to fail?
Lack of Clear Data Strategy
One of the most common reasons for analytics project failure is the lack of clear objectives. Without a well-defined goal, it becomes challenging to measure success or even know where to start. A well-defined data strategy helps to align stakeholders and create a clear roadmap for the project.
Poor Data Quality
Poor data quality is another major reason why analytics projects fail. The accuracy, completeness, and consistency of data used in analytics projects are critical. If the data is inaccurate or incomplete, the insights drawn from it will be unreliable, leading to flawed conclusions.
Inadequate Data Infrastructure
Analytics projects require a robust data infrastructure to support data processing, storage, and analysis. Inadequate infrastructure can lead to slow processing times, system crashes, and data loss, all of which can jeopardize the project’s success.
Lack of Skilled Talent
Analytics projects require skilled professionals with data science, statistics, and programming expertise. Organizations that lack the right talent will find it challenging to implement analytics projects successfully.
Siloed Systems
Their data is trapped in individual siloed systems limiting insights across multiple applications and domains
Resistance to Change
Analytics projects often require significant changes in organizational processes and workflows. Resistance to change can occur at any level of the organization and can impact the success of the project. It is essential to identify potential roadblocks early on and work to mitigate resistance to change.
To help companies solve data complexity problems, we’ve purpose-built One Six as their partner in building a Modern Data Organization.
Modern Data Organizations are committed to the idea that all business decisions must be data-driven. They have defined and executed a clear and deliberate strategy to centralize their data, extract meaningful and reliable insights, and develop a culture where high-quality insights are available and actionable at all levels of the company.
Developing an Enterprise Data Strategy that provides a clear and deliberate roadmap from your organization’s current state to where you want to be, is the critical first step for a successful analytics project, and to becoming a modern data organization.
The One Six team created our Data Strategy Roadmap process to help companies map their path from their current state to their desired future state. This process prioritizes projects with high ROI and low risk. Our strategists will collaborate with your team to determine the most impactful projects in the short and long term. They will create a list of prioritized projects using an opportunity matrix, which will show which projects deserve investment and the best order to tackle them.
Current State
The One Six team will analyze the existing data assets, strategy, platforms, people, and processes and create a scorecard of your organization’s data maturity.
Future State
The team will create a strategic vision for your data-driven organization’s future state, including technology, people, processes, and data use cases.
Roadmap
The team will develop a roadmap to move you from this current state to the future state prioritized by the projects that provide the most value.
Equipped with your detailed Enterprise Data Strategy, One Six has the experience, expertise, and personnel to help implement your data strategy roadmap and ensure success for your analytics projects.