Transforming Decision-Making Processes

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Read more about author Paula Hansen.

On a typical day, managers spend 37% of their time making decisions, according to a McKinsey study. Decisions are the lifeblood of a business and need to be made with accuracy and speed. The manual and complex process of decision-making today amounts to 530,000 days of lost productivity and roughly $250 million in labor costs for the average Fortune 500 company. So, how do leaders modernize their decision-making to achieve both quality and speedy outcomes from everyday decisions to the most critical challenges?

Leveraging Technology for Insights-Driven Decisions

Business and government leaders want more assurance and guidance when making these important decisions. A data analytics platform gives your team the tools to unlock valuable insights to make faster and more confident decisions based on data versus guesswork or intuition.

To better understand the role analytics plays in decision-making, my company commissioned a global study composed of 2,800 senior business decision-makers, IT decision-makers, data analysts, and line of business leaders.  

The study revealed an overwhelming belief that technology can help organizations make more confident and faster decisions. Not only can advanced technologies, such as analytics, machine learning, and artificial intelligence, help to expedite the decision-making process but the majority of respondents believe that analytics enhance data collection and analysis while improving communications across the business during the decision-making process.

Currently, business decision-makers, IT decision-makers, data analysts, and business users describe their data analytic capabilities as diagnostic, which involves techniques such as data visualization, data mining, and drill-down analysis to identify patterns and correlations. However, respondents believe that by 2030, predictive and autonomous analytics will be used more frequently. Predictive analytics will help organizations to anticipate future outcomes and make data-driven decisions to optimize their strategies.

Furthermore, by 2030, organizations’ leaders are expecting to have implemented artificial intelligence and machine learning algorithms to automatically execute decisions and actions based on the insights driven from the data – only 11% of all respondents are currently using autonomous analytics. They are the ones surpassing the competition and navigating the economic environment with strength and resilience.

Using Technology as a Competitive Advantage

Knowledge workers are looking for confidence and accuracy when making decisions within their organization. However, one of the top challenges faced by decision-makers and analysts is the quantity of decisions that need to be made.

The research found that it takes on average two days for companies to make an operational decision, seven days to make a tactical decision, and 20 days to make a strategic decision. The current economic landscape is in a state of uncertainty and organizations need to react and adapt quicker than ever. This means making more confident and accurate decisions at a faster speed. Taking two to 20 days to make decisions gives your competitors a chance to accelerate past you. Using technology such as synthetic data and generative AI (genAI) helps to speed up the decision-making process and allows all employees to feel more confident in their decisions. 

Using Synthetic Data Practices to Solve Business Problems

Mastercard is utilizing synthetic data to increase revenue, accelerate innovation, and build trust and understanding of data. Synthetic data is a type of Privacy Enhancing Technology (PET) that allows one to create a new data set that is as statistically similar as possible to the underlying data while not including personal data. 

At a recent analytics event, John Derrico, VP of Data Strategy for Mastercard, explained how synthetic data can be integrated into pre-built workflows, giving wider access to employees needing to make informed decisions. By using synthetic data, Mastercard has demonstrated an opportunity for organizations to administer data for better decision-making and diminish concerns about data privacy. 

This positive result comes as no surprise, as our research showed that 80% of the global total of respondents agreed that having the ability to access and analyze data has had a positive impact on decision-making abilities. 

GenAI and the Future of Decision-Making

GenAI has quickly become a part of everyday conversations from the boardroom to the kitchen table. One specific topic of interest is the role genAI can play in enhancing and improving an organization’s decision-making paradigm.

Organizations should look for AI engines that combine the power of artificial intelligence, machine learning, and generative AI to further advance the democratization of analytics. This can reduce the time required to derive insights from data. With AI and cloud-native analytics automation, the power and scale of better decision-making is at everyone’s fingertips. 

While it is still the early days for genAI, we see this newer capability accelerating the path for organizations to become more insights driven in their decision-making. Natural language processing translates insights into business language that can be shared broadly and leveraged by all. GenAI and large language models (LLMs) eliminate tedious tasks, leverage best practices from millions of workflows in production, automatically document workflows, and free up time for humans to focus on more strategic challenges.

The Future of Automated Decision-Making

Our research showed that 97% of business leaders envision a future where all decisions within the organization will be automated. Our research also suggests that 66% of leaders believe that the future of decision-making will remain a combination of humans and machines. The Greek philosopher Plato said, “Make decisions based on knowledge, not numbers.” With analytics automation, the power and scale of better decision-making is at everyone’s fingertips.