What’s next for analytics in 2023?

Will analytics teams conquer the last mile of analytics in 2023?

I’m overenthusiastic about the end-of-the-year wrap-ups and predictions. It’s the perfect time to zoom out from the daily grinding and see the big picture. I love reading articles on learnings and trends from my peers as well as industry leaders, taking time to review my year, and planning for the next one. So I wanted to share my take on what will be top of mind in data analytics next year.

2022 hasn’t been the easiest year for most. Due to the recession, we witnessed a high number of layoffs and budget cuts. “Doing more with less” became a phrase that we all used more and more. And I expect it to be the motto of 2023.

So, I predict an increased focus on efficiency, business value, and maximizing ROI for analytics teams. As a result, only projects and technologies that deliver the following will be prioritized:

• help teams save time and resources, increasing efficiency
• help teams save revenue and cut costs, maximizing data & analytics ROI Here are my predictions for some of the most important analytics trends heading into next year (in no particular order).

Prediction #1 — focus on proving the ROI of analytics

Data-forward companies made significant investments in technology and people over the last few years. Initially, their focus has been on collecting, storing, managing, transforming, and displaying data to establish a strong core.

Data quality is essential to creating meaningful results, but it isn’t enough to create business value. If we were to see the data analytics journey as a marathon and the business impact as the medal, delivering actionable insights that inform daily and strategic decisions are a must-have to complete the race. Hence this is where the leaders are shifting their focus to maximize the ROI.

So how can you get there?

• Closer collaboration with the business teams (e.g., nailing priority use cases together, and daily/weekly performance reviews to review and share insights)
• Speed and comprehensiveness in analysis to truly empower decision-making
• A strong focus on measuring business value and continuous iterations to achieve the best results

Prediction #2 — most decisions will be augmented with ML

To be able to keep up with the pace of data and business, the “doing more with less” motto surfaces once again. Businesses need to augment workflows and automate menial tasks, accelerate speed to insights and break out of speed and comprehensiveness trade-off to create true business value and maximize the ROI of data analytics.

Decisions that use data can be automated in a variety of ways and fall somewhere between being mostly human-based and entirely automated. ,

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