Executive Q&A: The State of Cloud Analytics

discuss the results of a recent Alteryx cloud analytics survey with Adam Wilson, SVP and general manager at Alteryx, to learn about why and how organizations are investing in cloud-based analytics.

Amid increasing economic uncertainty, data leaders are increasingly turning to the cloud to help them keep up with the demands of their roles. To assist in this effort, Alteryx conducted a survey in November of 2022 to find out why and how organizations are investing in cloud-based analytics. The survey included responses of 309 people who work for companies with 1000 employees or more and were currently using or planning to use cloud analytics. (Editor’s note: Access to the survey results is available here; registration is required.)

Upside: Your report says the fact that 89% of respondents said cloud analytics investments were contributing to profitability was “startling.” What is startling about this? What were your expectations?

Adam Wilson: For starters, the sheer consensus of the response -- 90% of respondents -- is a high enough response rate to garner surprise, especially when considering a topic as critical as profitability.

To set the stage, we need to take into consideration the context of the responses. Many businesses are trying hard right now to stay profitable during these times of economic uncertainty. The startling takeaway to us was that business and technical leaders see cloud analytics as the tool -- not a silver bullet, but a critical component -- for staying ahead of the pack in the current economic climate.

Not only that, organizations need to do more with less and, as it turns out, cloud analytics is not only a wise investment during good economic times, but also in more challenging economic times. Businesses reap benefits from the same solution (cloud analytics) in either scenario.

For example, cloud analytics is typically more cost-effective than on-premises analytics solutions because it eliminates the need for businesses to invest in expensive hardware and IT infrastructure. It also offers the flexibility businesses need to quickly experiment with new data sources, analytics tools, and data models to get better insights -- without having to worry about the underlying infrastructure.

Related to this, we believe this response rate suggests that business leaders perceive cloud analytics as a solution that can provide quick time-to-value, enabling quick wins and rewarding business value.

Single, comprehensive solutions for cloud analytics needs were preferred by most. What can you recommend for organizations that are already using one or more point solutions for their analytics?

The reality is that there are unintended consequences of relying on point solutions: vendor management becomes more complex given the volume of vendors and contracts to manage, employees must master multiple products to be effective, and hand-offs and integrations between different products must be established and maintained. All of these challenges can be mitigated by using a comprehensive, unified, and end-to-end platform that delivers the analytics capabilities an organization needs to be successful.

For these reasons, CIOs and CFOs will want to focus on vendors that offer platforms with the right analytics capabilities to mitigate risk and maximize reward.

We recommend using the current economic environment as an opportunity to double down on analytics in a scalable, flexible, risk-averse way by advocating for investment into a single, comprehensive solution that can replace the point solutions in your environment and provide the capabilities that all personas -- data experts and line of business users -- will need moving forward.

Ease of use ranked highly as something to look for in an analytics solution. What are some factors that make a solution easy to use?

Many vendors claim ease of use as a benefit of their software. In this context, we view ease of use as the ability to enable the highest number of people across the organization -- not just data analytics experts -- to be productive with analytics tools.

Because a high percentage of knowledge workers rely on spreadsheets as their primary tool for analytics, ease of use should take into consideration what is intuitive to a spreadsheet-reliant user base in this context.

From here, we can break ease of use down into several core components:

• Intuitive user interface and experience: The user interface and user experience should be intuitive, meaning users are not intimidated by the layout of the application. Feature functionality works as expected and is organized in a way that makes sense to an average business user, not just advanced data scientists.

• Little (if any) technical expertise required: This typically manifests itself in two ways -- either no-code/low-code applications that do not require specific technical skills to use or applications that embed AI into their business logic to reduce the amount of low value, repetitive, or mundane tasks for a user.

• Support availability: Effective channels exist to support users in their adoption at the pace of business. Extremely large and active online communities are a prime example. Others include robust customer service and support, premium vendor support, and active user groups.

• Shortcuts to build and deploy solutions: It is important to have a vast number of out-of-the-box connectors, which reduce integration work or additional technical support requirements.

• Extensive capabilities: Solutions should provide several capabilities that reduce the amount of time spent toggling back and forth between different tools.

We firmly believe that analytics should be accessible to all employees, and each of these factors makes analytics solutions easier to use by making them more broadly available to non-technical audiences across the lines of business. In turn, this increases the likelihood of adoption and reduces the amount of training required to use analytics to drive intelligent business decisions.

Almost all respondents said their organization would benefit from more users having access to analytics tools. How are they doing overall in achieving this goal?

We have some good perspective on this from our Analytics Maturity Assessment (AMA), an industry benchmark which we developed in partnership with The International Institute for Analytics (IIA).

Most respondents to the AMA said that only 11-25% of decision makers in their organization have access to data. However, organizations that have adopted cloud or hybrid analytics solutions report having more access to organizational data.

We see across any domain that cloud and hybrid solutions naturally lend themselves to centralization, greater democratization, and easier governance. They're built to integrate with both on-premises and cloud services. These benefits make cloud solutions more straightforward for organizations to deploy and manage across their enterprise -- making access easier to provision, manage, oversee, and roll out to stakeholders.

Collaboration tools in cloud applications were a main driver for adopting the cloud for many. What are some of these innovations?

Cloud solutions that can bring together data experts and line of business users, who are best positioned to extract gold from analytics with their domain expertise, will provide serious benefits to organizations.

Analytics is cross-functional by nature. Successful analytics initiatives typically require input and collaboration across technical experts, data experts, and domain experts. Traditionally, domain experts have been left out of the analytics process or engaged minimally at the beginning or end of a project, preventing them from uncovering the insights they need to make data-driven decisions.

Democratizing data and analytics is the key to solving this problem; it means multiple perspectives can contribute to a culture of analytics, not just the technical and data experts.

In the coming years we expect many high-visibility analytics projects to be highly cross-functional -- initiatives such as customer intelligence that require input from IT, analytics, marketing, sales, and finance. Cloud analytics inherently supports this collaboration by providing the opportunity for reuse of analytics builds, flexibility across an enterprise to provision/deprovision access to a platform, and the scalability to increase workloads as solutions become more heavily adopted.

What surprised you most about the survey results?

Three key takeaways in particular were surprising:

First of all, 81% of organizations surveyed expect cloud analytics to have a positive impact on managing economic uncertainty (potential recession, inflation, etc.). This is an overwhelming number of business and technical leaders that believe cloud analytics is one of the answers to the challenging times we face in the coming months and years.

This suggests that cloud analytics is not simply a “nice to have” when the economy is performing well. It is perceived as a critical capability that organizations need to stay competitive, survive, and thrive in today’s environment.

Next, 89% of respondents agreed that their cloud analytics investments have contributed to profitability. We already covered this in the first question, but to reiterate: businesses across industries are scrambling to be more efficient and effective in driving optimization in their organizations while trying to stay profitable.

It surprised us that business and technical leaders see cloud analytics as the tool to stay ahead of the pack in the current economic climate.

Finally, 64% of respondents cited improved operational efficiency as a cloud analytics benefit. This demonstrates that manual and inefficient processes continue to be at the top of the list as major challenges for organizations.

Organizations have been addressing this through digital transformation initiatives, but despite the progress that has been made, there is still a lot of opportunity to drive more efficient business operations.

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