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TDWI Upside - Where Data Means Business

How to Succeed with Data in 2023

Instead of getting overwhelmed by new data, use your data to your advantage so you can find more certainty and confidence in 2023.

A petabyte or more -- that’s how much data your company could gather in 2023. That might sound enticing. Data is often considered a significant business asset. However, data is only useful if your business does more than simply store it and explore it. Real value comes from effective uses of data that solve specific business problems.

For Further Reading:

Distributed Advanced Analytics Through Citizen Data Scientists

Welcome to the Age of the Engineer-Data Scientist

How to Avoid Inefficiencies and Engender Trust in a Data-Driven Enterprise

I predict that data-driven decision-making will face growing challenges in 2023, even while new technologies can alleviate those difficulties for businesses prepared to innovate. Data scientists’ valuable skills will be applied more effectively to nuanced data projects. Their efforts will be supplemented by the automation of routine machine learning tasks and ubiquitous use cases that transcend companies and industries. These changes will serve companies’ customer engagement and retention goals, which will be especially critical in 2023’s volatile environment.

Here’s my reasoning for these predictions, along with tips on coping with next year’s changes.

Prediction #1: For most enterprises, data-driven decision-making will get harder before it gets easier

The field of data analytics has seen rapid changes over the last decade. First, we saw the development of tools for connecting to and extracting information from single sources, primarily with BI tools for visualization and exploration. Then, tools emerged to unify multiple data sources, with insights surfaced in second-generation tools such as customer relationship management (CRM) software and customer data platforms (CDPs) that helped data analysts and data scientists develop historical analyses. Now more companies, especially larger ones, are bringing AI technologies into their teams, including data and analytics groups.

These critical steps are laying the groundwork for perhaps the most valuable generation of data technologies: those that can use this unified data to not just make predictions but to guide meaningful business decisions. By automating the data science workflow, these technologies use your data to accurately and rapidly guide daily choices and critical business strategy.

Most companies haven’t moved into this third generation of data technologies. They know there’s value within their overwhelming quantities of data, but most of their data projects are confined to what they can learn from second-generation data tools. They engage in lengthy, expensive explorations and modeling projects that yield occasional “actionable insights” but little meaningful guidance for everyday decisions and long-term strategy. In a recent survey we conducted with Wakefield Research, 84 percent of marketing leaders said that despite all the customer data they gathered, they found it challenging to make day-to-day, data-driven decisions and take action. These leaders struggle to gain real value from their data.

Companies will continue to increase the quantity of data they gather, especially as first-party data increases in importance. Their oceans of data will become deeper and broader -- and even harder to navigate for those whose data tools haven’t yet advanced.

However, companies ready to seize a competitive advantage will implement those third-generation data tools that guide specific decisions related to important KPIs and offer rapid ROI. Instead of spending time and resources on data efforts that may or may not provide results, they’ll choose technologies that efficiently inform their critical data-driven decisions.

How to succeed in 2023: Which generation of data technologies is primarily in operation at your company? Evaluate the methods you currently use to unify and analyze your company’s data. Ideally, these methods provide not just insights about the past but an informed, future-focused perspective to guide data-driven decisions about strategy. Identify the KPIs for which a future-focused perspective would be most valuable and focus data projects on driving positive impact on those goals.

Prediction #2: The “generalist” data scientist will become more specialized

Today’s data scientists have been required to work on a wide range of data projects. However, the growing adoption of the next generation of data technologies will mean that data scientists will instead dedicate their skills to more nuanced, “artisanal” projects involving hand-crafted predictive models. In these cases, special attention may be warranted because a use case doesn’t have a reliable, accurate, automated solution (yet) or because it requires particular domain expertise. Data scientists’ work offers the greatest value to these kinds of projects.

For Further Reading:

Distributed Advanced Analytics Through Citizen Data Scientists

Welcome to the Age of the Engineer-Data Scientist

How to Avoid Inefficiencies and Engender Trust in a Data-Driven Enterprise

For projects that are essentially “rinse and repeat” -- where there is a well-established, automatable machine learning workflow -- there are more efficient paths to success. Predictive analytics software is a great example, especially for a range of fairly ubiquitous customer-journey use cases. Businesses can generally implement these cost-effective options far more quickly, generating value in a fraction of the time required for “artisanal” data science.

Data scientists will likely still be in high demand to take on complex tasks across departments at their companies. Yet, at the same time, difficult, long-term, expensive projects will be thoroughly scrutinized by businesses of all sizes. In 2023’s challenging conditions, companies must ensure the wise use of resources and reduce the risk that they might invest in projects that never make a real business impact.

How to succeed in 2023: Optimize data science resources by supplementing expert data scientists in your organization with data tools that automate routine elements of data science work with trustworthy methods. This approach minimizes costs, ensures the best use of data scientists’ time and capabilities, and brings machine learning and predictive modeling capabilities into teams that have direct impact on revenue and profitability.

Prediction #3: Companies will focus on how to efficiently retain existing customers

Given the market volatility, data analytics and marketing teams will almost certainly face reductions in budgets and headcount in 2023. Those who remain will be under substantial pressure to deliver results. At the same time, these tough economic conditions mean that customer acquisition will be more difficult and costly.

Doubling down on their biggest asset -- their existing customers -- will provide companies the most opportunities to maintain or grow revenue in 2023. By retaining their current customers, engaging them more deeply with their brands, and increasing their share of wallet, companies will achieve their best possible results.

Consumer behavior will no doubt be erratic in 2023. With inflation, changes in the cost of living, and likely reductions in buying power, customers will quickly adapt and develop new behaviors and patterns. Companies relying on BI-driven business rules will find their rules to be swiftly outdated.

It is possible to rapidly predict and proactively respond to customers’ changing behavior. Future-focused, prescriptive technologies that use customers’ behavioral and transactional data to determine highly likely future outcomes will guide more agile strategies as customer currents shift. That’s especially true for businesses with high-frequency, repeating customer behavior such as retail and e-commerce. A steady stream of data can fuel an automated workflow that injects predictive insights about customer behavior directly into business systems, generating reliable data-driven guidance for business decisions.

How to succeed in 2023: Ensure your customer retention and engagement strategies are dialed in and ready for rapid adjustments. Sudden changes will be inevitable next year. Your data will be a vital part of making proactive, future-focused decisions that respond to what your customers will likely do next, instead of just trying to react to what they’ve already done. Implement systems that give you the foresight to identify, interpret, and plan for these changes in advance.

Making the Unknown Known

We’re still enjoying the last weeks of 2022, but 2023 is already preparing its twists and turns. It’s time to get ready for whatever may come. With the right data strategy, you’ll be able to recognize emerging patterns early so you can take proactive measures instead of being caught off-guard and unprepared. Advanced data tools and predictive approaches that can inform effective decisions and actions already exist today. Instead of ignoring or getting overwhelmed by those petabytes of new data, use the data you have to your advantage so you can find more certainty and confidence in 2023.

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