Why budgeting for data analytics will grow business | Talend Blog

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With so many people in so many parts of the business with a variety of data analysis skills wanting access to data for business intelligence, IT is expected to provision access to it all. However, IT’s budget and resources are relatively flat. There is a growing gap between business expectations and what IT can deliver.

Data analytics is evolving from a “nice to have” capability to an imperative “must have” business function. In 2020, many enterprise budgets will be focused on investing to increase the analytical capabilities of its sales and marketing groups. In fact, we are now expecting a Compound Annual Growth Rate (CAGR) of 28.2% for streaming analytics between 2019 and 2024. This can only mean that IT will have to relinquish some control of its budget to these other groups in the enterprise. Yet, how can IT demonstrate its ROI to the rest of the business?

According to the 2019 Harvey Nash/KPMG survey, IT control is shifting, and more companies are moving toward business-managed IT. More than 20% of the survey respondents say 11-25% of tech budget is managed outside of the IT department, by other groups hoping to capitalize on data analytics to grow their part of the business.

With all these additional departments more interested in data than ever, investment in "new tech" categories is on the rise. By next year, the market is expected to hit the $1 trillion mark, according to IDC's global spending forecast for 2018-2022.

To ensure IT and data initiatives earn the go-ahead from top leadership, tech managers must prove efficiency outcomes, and provide business cases grounded in data as they push for 2020 investments.

The onus is on the respective department – whether it is IT, sales or marketing - to prove technology investments and the resulting data analytics will have a positive impact on revenue.

Ultimately, asking for more money for technology deployments requires a demonstration of return on investment. There are many ways that ROI of technology funds can be measured, and some are less obvious than others

A sure-fire way to demonstrate the efficacy of the a technology investment is to give a clear example. The simple argument is: Advanced analytics and machine learning help make things much simpler. And simpler means savings. Democratizing data governance and data management ultimately improves developers’ productivity and empowers non-data experts to work with data. Also, by suggesting next best actions, users are guided through their data journey.

Let’s take an example from Talend Data Preparation; when the software identifies, by introspecting the data, that it might be worthwhile to standardize the value of data in a textual column, it suggests that the user try the function “find and group similar text”. This function uses an advanced data quality function called text clustering. Through the use of smart functions such as pattern recognition or recommendations, the software can make this sophisticated function useable and relevant to a non-data savvy audience. 

The end result is an organization of enabled business and IT users making critical decisions based on accurate data in less time. This is the formula for increasing revenue and driving business growth.

Additional technology funds won’t mean a thing if it is not directed to the right areas. A core objective should be to use data integration and mining solution that will deliver trusted, intelligent data for your important business decisions. Without the right tools to drive your business forward, adding more technology to the mix is a waste of time and effort – and budget.

Learn more about why data integration is critical to your business strategies.