Recent findings from North Carolina State University indicate that in most companies, Excel is still the go-to analytics tool. Each employee spends 2.5 hours daily just searching for relevant data. However, the majority of executives are taking a “wait and see” approach to adopting advanced technologies into their workflow.
While not entirely surprised by the results, we were a bit disappointed. After all, in an era of rapid technological change, you would expect most business leaders to readily embrace digital transformation and for organizations to recognize the importance of data in that initiative. But the recognition and the reality are obviously two different things.
In what follows, we’ll summarize key takeaways from the report, the 2nd Annual Data Governance, Data Quality and Artificial Intelligence in the Supply Chain, and why companies must take a more proactive stance when it comes to data and analytics, rather than just “wait and see.”
Organizations that get digital transformation right must master the art of data quality first. In fact, 75% of businesses say poor data has made it challenging to adopt advanced technologies like AI.
Many organizations are making “incremental efforts” in this direction, but it’s not enough; they really need to fast-track things to keep up with the momentous pace of Big Data.
Data analysts typically spend 60-80% of their time cleaning and organizing data to gain some level of confidence in their insights. Even more frustrating is that the average employee spends 2.5 hours a day just looking for relevant data.
Over the course of weeks and years, this adds up to thousands of hours of wasted productivity. The lost time isn’t the only negative consequence, either. It leads to bad decisions or missed opportunities when people cannot access the data they need in a timely manner.
Companies must develop a “unified approach” to data governance that treats it as a critical asset. Using automated processes for collecting, cleaning and harmonizing data in a single place is a good practice for ensuring quality information across the enterprise.
Data without people who know how to use it is worthless. However, the report shows that “data related training for employees” dropped significantly between 2017 and 2018, from 55% to 29%. What’s more, Excel is still the most dominant analytics tool for 50% of companies.
To make up for the lack of training, companies today must focus on supplying their employees with intuitive, user-friendly tools that anyone can easily pick up and start using for analyzing their data. Often, these are purpose-built tools for specific applications, like sales and supply chain management, rather than a tool like Excel that’s not set up for any particular use case.
The study noted that many executives still take a “wait and see” approach to enabling advanced technologies. However, this mindset is very risky, especially given executives’ growing perception that their competition is overtaking them – an increase from 47% in 2017 to 80% in 2018. These numbers are consistent with what manufacturers report in a recent IDC Market Spotlight; they expect an existing competitor (60%) or a digitally native new market entrant (54%) will leverage digital supply chain transformation for competitive advantage within the next five years.
The time to get started was “yesterday” as the velocity and volume of Big Data is increasing exponentially. In fact, 80% of all data is unstructured data or “dark data” that is hidden and hard to uncover. Developing the right combination of tools, technologies, people and processes to get at this information won’t “just happen” by itself.
This perfect storm of poor data quality, lack of proper employee training and lost productivity searching for elusive real-time data will not be sustainable over the long-term. Data is a critical asset that you must manage like any other form of company revenue and ROI.
Here is what is arguably one of the most impactful sentences in the entire report:
To move forward, small steps involving proof of concepts with AI should be adopted by teams of functional leaders. Such efforts do not have to start with or always involve significant investments, and could be exploring the use of [existing] tools . . . while starting to adopt advanced analytics solutions.
There is a lot here to consider, so let’s break it down into three primary points:
At the end of the day, waiting will cost increasingly more time, effort and money to address poor data governance as the problem only compounds upon itself. Much more, in fact, than if you proactively start investing in time-saving tools and technologies to achieve good quality data that teams use. These initiatives will not only lead to better business decisions and ROI, but will also happier and more engaged employees.
If you’re struggling with access to quality, up-to-date data, or are looking for an analytics tool that can help any user leverage that data, then we have a solution. Start your journey here today.
The global confectioner mitigates waste, improves service levels and controls costs by connecting digital supply chain visibility with POS analytics.
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