People and process, the biggest barriers to becoming data-driven

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People and process, the biggest barriers to becoming data-driven
In today’s digital economy, the ability to use data is a real and critical competitive advantage.
Photo by Alina Grubnyak on Unsplash

It is often said that data is the lifeblood of any organisation.

Yet having troves of data is little value in and of itself. What really separates the data-driven leaders from the data-rich companies is the ability to transform data into insights about customers’ needs and turn those insights into business strategy.

This alchemy requires a process called data science. As the volume of data increases and as new AI, machine learning and big data capabilities emerge, companies are employing data analytics to elevate the customer experience, enhance workplace productivity and drive business model innovation. Against an economic backdrop of COVID-19, deploying data as a strategic asset has become business-critical.

Despite increased investment in data capabilities and technologies, many companies are stalling in their ambitions to become data-driven. In fact, recent research by IDC and Alteryx highlights that more than 90% of Australian business executives believe that analytics is important for their organisations to remain performant. Yet only 20% of Australian organisations have achieved high analytics maturity.

To understand the root of this slow progress, IDC assessed companies against four key dimensions of data-driven business transformation: strategy, the presence of a carefully planned data and analytics strategy; data, the quality of data and how it is governed; workforce, the tools used to empower people to do jobs faster and better; and process, the automation and standardisation of key business processes.

Majority (90%) of the companies surveyed said that the cultural dimensions today – workforce and process –represent the biggest barriers to data analytics initiatives and the ability to derive long-term business value. Many companies report that understanding which data to use, building the right skills for analytics initiatives and reinventing business processes, is hindering true organisational data transformation.

Taming the deluge of data

The sheer volume and complexity of data has pushed businesses to the point where they can no longer perform analytics manually. Organisations are now sifting through a deluge of structured and unstructured data coming from multiple new sources such as sensors and social platforms. On average, companies have nine unique data sources that need ingesting, with 26 new sources or targets required per month.

For corporate data leaders, determining which data to use, how to source it and how to get it into an integrated form that can be used across the company is the first challenge. Companies can benefit by focusing their data initiatives on clearly identified business use cases and work with all departments to understand where there is a critical business need to build business momentum.

Building data literacy among leaders

Data analytics initiatives are also hampered by low data literacy and skills. When asked about the key challenges they faced, 55% of Australian leaders cited hard to use tools, 49% said lack of access to timely data and 43% said data literacy. Data literacy among leaders is a significant driver of corporate growth and leaders need to be well versed on their data strategy and governance.  

Most importantly, organisations need to educate their entire workforces with critical data skills that drive business outcomes. Not every worker will build analytical workflows, but every worker should be able to ask questions within their functional area, such as what percentage of our customers churn each hour or day or do we have the right inventory in the right warehouses to optimise delivery times?

As there is increased data democratisation, data workers also require accessibility to answers. Every executive and employee needs to have access to automated insights via dashboards, reports and views in enterprise applications. Data will be useless without a solution that empower everyone with real-time insights.   

Break down data silos

Many data analytics programs also suffer from data silos and ad hoc processes. It’s common to see some teams using multiple spreadsheets, or others cleaning and analysing data with fragmented tools. For many organisations, it can be complex – and even costly – to reconcile and integrate sets of data that embody different approaches while aligning to business concepts.

To remove organisational silos, an outcomes-driven analytics strategy that focuses on the business outcomes and puts people on the front lines is most effective. In addition, to identify high-impact business uses, companies should build towards an integrated and automated platform for their enterprise data, working with the support of executive leadership and functional leaders across IT, sales and marketing.

In today’s digital economy, the ability to use data is a real and critical competitive advantage. The organisations that invest in upskilling their workforce, rethink their integration strategy and automate business processes will be able to build analytics maturity and sustain long-term commercial success by delivering business value.

Julian Quinn is Senior Vice President, APJ at Alteryx.

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