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Executive Perspective: Simplification and Data Tools Will Be the Focus for Business in 2022

How will businesses simplify their analytics environments to improve business efficiency? Heine Krog Iversen, founder and CEO of TimeXtender, offers some ideas.

• By James E. Powell
• December 8, 2021

What do industry executives think that 2022 will look like for data and analytics? Heine Krog Iversen, founder and CEO of TimeXtender, considers the notion that businesses need to simplify their data/analytics environments to get more from their data and improve business efficiency.

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Upside: How would you summarize the last year or so regarding enterprise data and analytics?

Heine Krog Iversen: There's been a movement by more companies to efficiently and quickly collect, store, and use their data more advantageously for analytics, AI, and ML. Part of this process has been an acceleration to move to the cloud.

Businesses are realizing that a comprehensive data platform, or what we call a data estate, establishes a modern architecture for managing corporate data. Data estates also enable tighter security and better governance than having data dispersed throughout the enterprise.

Most agree that data is a primary asset for organizations to become more competitive and productive, yet the debate continues regarding the best way to manage it. Although we see great improvement when centralizing data into a single platform, far too many companies still have data siloes and various platforms.

To exacerbate this issue, we see new products and tech terms being invented and introduced that companies are buying into without fully understanding what these innovations mean for their businesses. Many CIOs are eager to claim that "Yes, our IT implemented that technology in our business," but this can cause numerous issues and confusion for an organization. When considering new data and analytics technology, businesses should lead with the question: What challenges and problems exist that can be solved by this technology?

What was the biggest surprise that transpired across the industry regarding data issues?

The surprise has come from businesses on the end-user side. I hear all the time how an organization is closing in on 150 different applications to run their business and then one day executives step back and ask, "What are we doing here? We have all these applications, all these data sources, and now our tech environment is too complex." At this juncture, some argue that they have too much data! Having too much data is not the issue, but rather it's that the business is not fully understanding the best way to manage it.

Data should be collected, stored, and managed in a centralized, single platform to help simplify the data environment and reduce complexities, while also improving security, privacy, compliance, trustworthiness, and control. The old way of having IT in the basement and giving chunks of data to business users upon request is just that -- the old way. Business users need to be empowered to have instant access to data, albeit in a controlled and governed manner.

What trends do you see emerging in 2022 that will impact data and analytics?

First, I think assimilation in the cloud (accounting for data warehouses, data lakes, and other platforms and apps) is still a top priority that will continue.

We will likely see an even greater shift towards no code/low code solutions to reduce the complexities of development and businesses flipping in and out of numerous applications. There will be a louder cry for more support so that businesses can combine and manage their data in an easier, more efficient manner. Drag and drop and automation will have keen roles as well.

I believe more companies will invest in AI while others that have worked with AI will ask: "Are we getting what we set out to get from AI?" Some of the businesses that are further along the adoption curve will wonder if the AI algorithm possesses inherent bias that decreases trustworthiness and will assess if AI is a dominant factor or merely just one factor in helping to map out the future.

It has been said that data engineers spend 80 percent of their time preparing data for use for analytics and AI, so I expect businesses will look for ways to shift these resources to more game-changing initiatives. People will try to make their platforms part of an integrated environment with better data management throughout their landscape, business layers, and applications, leading to efforts to remove complexities.

How would you advise technology management to prepare for these 2022 trends?

I believe it is about approach and mindset to solving business issues. We need to get business people to understand that you can simplify processes and break down complexities for collecting data and building a supportive environment. This process begins with industry education. Many policies and processes are outdated, yet organizations keep adding applications, technologies, and data across the organization and throughout departments to their archaic data architecture. At the same time, it can be hard to find qualified people to help manage all this technology and the ones who are there often spend far too much time preparing data, manually coding, and repeating tasks.

When you add all this together, I think tech management needs to step back and become more informed about simplification. This starts by admitting that they need to be more open-minded, inquisitive, and explorative. Businesses need to think long and hard about how they can change. There are lots of smart people in the business world with strong opinions about how to manage their data, yet many are very frustrated with how complex their data environment has become.

Technology evaluation should begin with some fundamental questions: What are we trying to solve for the business and what is the best way to proceed? How do we add the most value and efficiency for the business?

Meeting deliverables for implementing new technology is not the end game, yet many companies gauge their success on just that.

If you had to write a headline for what we'll see in data and analytics in 2022 what would it be?

The year of the data tools.

More specifically, data tools for the business side not the tech side. Separately, I expect to see more: automation, no code/low code, and drag and drop -- all with the intent to implement and manage data more easily so that a business can focus on more strategic breakthroughs and initiatives. This is important because time matters.