7 ways to unlock new business value during economic turbulence
As CPI hits its highest level in more than 40 years and fears of an impending recession intensify, IT spending has nevertheless continued to grow and is expected to continue growing another 5% in 2023, according to Gartner.
Because the right technology accelerates time to value, increases productivity and unlocks new business value, more than two-thirds (69%) of CFOs surveyed in a 2022 Gartner poll said they would be stepping up spending on digital technologies, even amidst the prevailing economic turbulence.
While spending in technology will continue, many companies have and will continue to make adjustments to their operations and cost structures in response to inflation, including doing more with less.
A smart data and analytics strategy leveraging the right technology enables companies to stay competitive and profitable while continuing to better meet the needs of their customers. Below are seven ways businesses can accomplish this in 2023 and beyond.
1. Move from a transactional relationship with customers to a personalized one
Advanced data analytics and artificial intelligence allow companies to track, analyze, optimize, personalize, and monetize processes and customer touch points that were previously unexploitable.
By leveraging historical models based on past data as well as predictive models using regression analysis and machine learning to forecast buying behavior and gain new insights, companies can do a better job of understanding, anticipating, and meeting their customers’ needs at every point along the buyers’ journey.
2. Foster a digital mindset in the workplace
The skills gap in the labor market is not going away on its own. It is up to companies to provide the training necessary to uplevel their workers’ skills and data literacy. Successful digital businesses require a data-literate workforce and a data-driven culture to drive measurable business outcomes.
According to Professors Tsedal Neeley and Paul Leonardi, digital skills alone are not enough. Workers must also have perspectives and attitudes that motivate them to use their skills to create new business opportunities. This is a cultural facet they refer to as a digital mindset. This not only involves training, but also an alignment of digital mindset-enabling systems and processes.
3. Use advanced visual reporting to understand business operations and your customers
For leadership to have a finger on the pulse of their business, they need to use sophisticated data analytics and visualizations fed by timely data collected from internal and external sources.
Traditionally, companies tend to use resource-intensive reporting efforts that, more often than not, fall short of delivering the data’s full potential value. In addition, insights can be difficult to access since they are “buried” under an abundance of data. Consequently, the focus is on descriptive analytics using hindsight as the primary point of view, resulting in a reactive rather than a proactive, predictive approach.
Advanced reporting enables the use of statistical methods to generate value from insights that may otherwise remain buried within the data. Enhanced decision-making can be achieved with a focus on the future through AI-enabled predictive analytics (rather than hindsight), delivered in an easy-to-understand graphical format. All of this results in faster access to insights, quicker responses to market shifts, and an increase in innovation.
4. Empower business users with self-service analytics
Traditionally, to gain valuable insights from a company’s collected data, one must work directly with IT or engineering teams to request a report. This is often a high-friction, resource-intensive process that delivers delayed results, possibly several weeks later.
This data can be democratized to give certain business users direct access to data sets that are described and cataloged fully to increase their value and validity. This enables users to self-service and generate reports as needed, based on accurate and up-to-date data.
Many BI and analytics tools have self-service capabilities to help users analyze data quickly and easily. One example is Tableau’s Ask Data. Ask Data leverages natural language algorithms to determine what a user is trying to “ask of the data.” You can ask simple questions like, what was the revenue for the last quarter? Or, what was net profit by a product line for the last quarter? And so on.
5. Harness collective intelligence through collaborative dashboards
Collaborative dashboards allow teams to quicky and seamlessly interact and share data assets and their stories; for example, through native integration with Slack or Teams for in-app report sharing, note taking, action items, and more. This enables teams to interpret data in a collaborative manner, benefiting from the group’s collective intelligence and diverse perspectives.
6. Migrate to modern cloud technology if you haven’t already
Cloud-based analytic platforms are designed to address the challenges of scalability, concurrency, and performance of conventional on-premises data warehouses and BI solutions. Legacy reporting solutions lack the easy-to-use-and-customize user interfaces, prototyping tools and self-service BI that cloud platforms provide.
Data practitioners benefit from cloud technologies that provide virtually unlimited amounts of computational resources. Businesses get results quickly without getting bogged down by the demands of all the infrastructure setup involved.
In addition, cloud platforms enable the elimination of data silos by unifying data ingestion, big data analytics, and data warehousing for secure, fast, and easy data sharing and analysis in one place.
7. Hire a chief data and analytics officer (CDAO)
A chief data and analytics officer (CDAO) is accountable for the data, decision sciences, insights, and related disciplines that enable better analysis and decision-making throughout the organization.
Unlike a CTO or CIO, CDAOs are not concerned with networks or hardware; they focus instead on the data within the enterprise tech stack. Ideally, they should be technology- and platform-agnostic, caring instead about business outcomes.
Centralizing data accountability and governance helps overcome the challenges that arise from siloed (and often incompatible) data policies, architecture, and management. Regardless of the prevailing economic environment, companies cannot stay ahead of the game without continuously adapting, and the right technology and data governance helps them do just that.
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