Businesses rely on departmental insights to make strategic business decisions. With an increased dependency on data for decision-making, organizations realize the need for easily shared, up-to-date information. According to a Global survey by McKinsey, focusing on the topic of organizational decision making, only 20% of respondents say their organizations excelled. Additionally, a majority convey that much of the time devoted to decision making is used ineffectively. Understanding why decisions are made is key for organizations to thrive. AI-powered analytics offer insights to make good data-driven decisions.
Decision Intelligence
Gartner estimates that by 2023, more than 33% of large organizations will have analysts practicing decision intelligence, including decision modeling.
Decision intelligence allows organizations to make informed, insights-driven decisions based on data. Combining data science, intelligence, decision management, and modeling helps drive positive business results. Decisions are modeled through a structure of integrating data, AI, and analytics. Data, actions, and outcomes are used to enhance the decision-making process. The 3 levels of digital intelligence are:
- Supporting business decisions
- Augmenting business decisions
- Automating business decisions
AI and ML both support decision intelligence enhancing forecasting and predictive ability. Organizations use decision intelligence to help automate and accelerate their decision-making processes across a range of use cases throughout different industries.
Decision-making is key for organizations as it can directly affect many facets of their operations. McKinsey reports that, on average, organizations waste $250 million annually due to poor decisions. Costs are just one reason businesses need decision intelligence. Predicting outcomes helps organizations to better frame their own potential successes by preventing wrong decisions from being made. With data, companies are prepared to make decisions that enable them to perform better than their competitors. Organizations use data intelligence to gain a greater understanding of their customers and employees.
Utilizing decision intelligence, companies can:
- Extract insights from information and data
- Escalate user engagement
- Create and implement decisions
- Extract insights and learn from previous decisions
- Advance the effectiveness of decision-making capabilities by comparing predictions to actual outcomes
Benefits of Decision Intelligence
There are many benefits to decision intelligence, let’s explore:
- Mitigates mistakes and biases
Bias can sway decisions, affecting outcomes. Why is decision intelligence so vital when we talk about bias? In the natural decision-making process, bias and mistakes can negatively impact results. Through no fault of their own, humans unwittingly inject their own personal bias.
How then can organizations make better decisions? Decision intelligence can help organizations to make better, more effective decisions that bring value to their operations. Unlike with the natural process, decision intelligence mitigates mistakes and biases by avoiding human conflicts and using programmed algorithms.
- Speeds decision-making process
When several individuals are involved in the decision-making process, it can be slow and cumbersome. However, the introduction of AI and data can quickly increase the speed of decisions. Valuable data-driven insights are key to making good decisions.
- A multitude of options available
Decision intelligence uses AI algorithms for the entirety of the decision-making process. With a multitude of options available to solve problems, organizations can choose the best strategies to not only solve immediate needs, but to also address multiple problems that often happen simultaneously, build on their internal processes, and improve their overall strategies.
- Aids with data-driven decisions
On a regular basis, organizations that make data-driven decisions excel. Data can be overwhelming, but utilizing good data, extracting insights, and driving impact are key to success. AI and augmented intelligence help businesses to make insightful decisions based on factual data.
3 Step journey to drive AI powered decision making at an Enterprise level
- Information – Make Analytics Pervasive
It’s imperative to have good data and create a strategic data plan. Data is critical to any digital initiative. The right data foundation and architecture helps enterprises to implement digital initiatives. In this technologically driven, digital age, organizations lacking modern data capabilities are at an immediate disadvantage within their industries. Enterprises need to invest to make analytics pervasive by data curation and visualization of structured and unstructured data sets.
- Extracting insights from information – Make Analytics Advanced
Enterprises can harness the power of advanced analytics with the help of AI and ML. The real keys to drive better decision making are AI-enabled advanced algorithms.
- Driving Impact – Make Analytics Invisible
The last mile is to Institutionalize Analytics to drive automation/semi-automation. Data allows enterprises to accelerate automation and commercialization. Making AI invisible by seamlessly operationalizing ML models in the decision making process helps to create a culture of action based on insights from data.
Component to be Considered to Create a Data and AI Driven Decision-Making Culture
Consider how the following services allow business to improve their data modernization efforts:
- Data Strategy – Data strategy enables businesses to chart data modernization paths and discover the future of data in their enterprises.
- Data Engineering – Data engineering can help solve data challenges, improve end-user satisfaction, and help businesses to make insightful business decisions with flexible and scalable data platforms.
- Data Visualization – Data visualization enables businesses to discover data-driven insights in a simple and intuitive manner. Data tells the true story!
- Advanced analytics and AI/ML – Advanced analytics and AI/ML allows businesses to leverage the latest data techniques to accelerate digital initiatives and maximize business outcomes.
- Data Management and Governance – Data management and governance helps organizations shift from controlling to managing their data. Collecting and building a data governance strategy is a powerful asset.
- Managed Data Services – Managed data services help businesses to Improve their data operations and core business functions without worrying about underlying IT infrastructure.
Businesses consistently look for ways to grow and stay ahead of the competition. Leveraging AI is one way to enhance future business planning. A digitalization and management strategy helps businesses to leverage AI. For the implementation of machine learning and AI, it’s key for businesses to have a good data set and a strategy to go along with it.
Organizations that leverage AI have seen success in their digital marketing efforts. With AI, marketers have used data successfully to identify new customers, create personalized messages based on their needs and amplify the entire customer journey. McKinsey Global Institute suggests AI can deliver real value to companies willing to use it across operations and within their core functions.
Data is the Differentiator
Having the right data at the right time helps to ensure organizations make the correct strategic data-driven decisions. AI makes it easier for organizations to share insights across the organization. As departments work together, AI turns data into a collective bank of information, from which employees can learn daily and make decisions that elevate departmental performance.
Apexon helps enterprises plan, execute and continuously improve their data modernization efforts, ultimately enabling organizations to make more effective, data-driven decisions. To learn more about data visualization, check out Apexon’s Data and Analytics services or get in touch with us directly using the form below.
