by Pedro Pereira
The digital race is on. To pull ahead of the pack, a company needs to know what to do with its data. Without a data-driven strategy, you’re bound to lose ground to competitors who apply their data to operational improvements, product development, go-to-market strategies, and the customer experience.
It isn’t enough to collect, interpret, and act on the data. You have to do it fast. The quicker a company can draw insights and act on them, the better it can respond to shifting market dynamics and evolving customer demands.
In this race, enterprises have an advantage. Bigger budgets give them easier access to the tools and expertise that support data-driven organizations. Strapped by tighter budgets, smaller companies tend to focus on keeping the doors open from one day to the next. Long-term strategizing is a luxury for many of them because business leaders hardly have the time to raise their heads from their daily obligations.
This creates a digital divide between the data haves — large enterprises — and data have-nots — smaller companies. But the gap can be closed. Savvy medium-sized businesses have opportunities to implement data tools as they become more widespread and affordable.
The returns are tangible. 86% of the companies adopting big data and data analytics state that adopting the technology has had a positive impact.
Challenges
Enterprises usually have the early edge in technology adoption, but it’s when the technology reaches down to midsize organizations that it enters the road to ubiquity. Big companies provide the testing ground for their smaller counterparts. If the technology proves beneficial, it will get the attention of these leaders, who are traditionally more judicious about spending.
The majority of business leaders who participated in the IDG’s 2021 Data & Analytics Study are data haves — 86%, an increase from 68% in 2016. But once the company size is taken into account, the numbers change. 93% of enterprise leaders have taken advantage of their data, compared to 81% of leaders of smaller-size companies.
Before mid-size firms can start spending on data management platforms and analytics tools, they seek assurances of a pay-off. And that means overcoming the challenges of implementing data-driven strategies:
- High Price — Data collection, management and analytics can get costly. Unless businesses can absorb these expenses, they cannot gain the insights needed to become more agile and competitive.
- Data Management Complexity — Collecting, organizing and integrating data is a complex undertaking. Even if companies have access to the right tools, they still need help in figuring out how to manage the process.
- Data Interpretation Roadblocks — Data collection and organization only gets a company so far. Without the tools to analyze and interpret the data, you can’t get actionable insights.
Mid-size enterprises are looking for tools that are simple, intuitive and automated. For maximum effect, these tools must be usable not just by data scientists and analysts but different people across the organization who need data to do their jobs.
More Data, More Problems?
The digital have-nots have one major advantage over the haves: They can learn from early adopters.
They may draw lessons from organizations that solved issues such as getting overwhelmed with too much data and struggling with organizing it. They have access to a wider variety of tools to help resolve these issues.
For instance, a company is likely to conclude it makes more sense to implement a data management platform than an amalgam of point solutions that may or may not work together. Such a platform, like the Cloudera Data Platform (CDP), processes and analyzes data from a diversity of sources, tracking the data’s origins and lineage for reliability purposes. With a proven track record from big enterprises — from Deutsche Telekom to GlaxoSmithKline to Experian — CDP can also help smaller companies to overcome the challenges of implementing data-driven strategies.
With Cloudera DataFlow on CDP, businesses can get access to scalable real-time analytics and actionable intelligence, from the edge to the cloud. Another tool, CDP Data Visualization, expands access to data analytics and predictive insights through machine learning (ML) at no additional costs or the need to purchase third-party tools. For businesses that have access to these tools, they can gain an edge in the digital race and work to close the gap between digital haves and have-nots.
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