Today’s IT wallet has more suitors than ever before. The barrage of recent headlines around identity theft and data breaches has underscored the need for stronger security measures.
The evolution of the mobile and remote workforce has caused companies to rethink their investments in networking infrastructure and mobile devices and increased regulatory requirements, along with the explosion of enterprise data, necessitate a robust and reliable storage environment. All of these larger categories have serious merit when it comes to technology investment but more organizations these days are looking to bolster their ability to actually do something with the data via business intelligence and analytical activity.
In a recent report I compared two user groups from our latest survey; those that had allocated greater than 10% of their IT budget toward big data and analytics (19% on average) and those with less than 10% earmarked for analytics (5% on average). One of the most interesting findings to come out of the report was that companies with higher BI allocation were performing better, almost across the board.
The return on analytical investment is manifesting itself in data quality, speed of information delivery, revenue growth, and profitability as well. The inevitable question then becomes – where does the money go?
Even under the category of big data and analytics, companies have a variety of spots on the roulette wheel to spread their chips. Investment in dashboards and visualization tools can help engage line-of-business decision makers. Data exploration and discovery tools are instrumental in empowering business analysts and data scientists.
However, the research shows that companies are more likely to put their money into the data to ensure a solid foundation upon which to build better analyses (Figure 1).
Figure 1: Analytical Enablers in Place
Time and again the research points to data management activities as critical pieces of the puzzle when it comes to business analytics. With the rapid influx of data most companies see, and the variation of sources and data types involved, companies turn to technology to help capture, organize, integrate, and normalize that information.
Data quality and cleansing technology helps combat the “garbage in, garbage out” pitfall of analytics and build more confidence in key decisions. Additionally, companies are leveraging web-based technology to help share and distribute data across organizational silos and enrich their most critical decisions with a broader range of supporting data.
I certainly don’t envy the technical leaders who have to make regular Sophie’s Choice decisions on allocation of scarce IT budget these days, but the research does strongly suggest that data management and analytics are not only valid areas to earmark funds, but arguably among the most important.
Take a look at the full report here: Dollars for Data: Budgeting for Analytical Excellence