As businesses take a global route to growth, two things happen. First, the complexity and unpredictability of business operations increase manifold. Second, organizations find themselves collecting more and more data — predicted to be up to 50% more by 2025. These trends have led businesses to look at Artificial Intelligence as a key contributor to business success.
Despite investing in AI, top managers sometimes struggle to achieve a key benefit — enabling them to make critical and far-sighted decisions that will help their businesses grow. In an era of uncertainty, traditional models cannot capture unpredictable factors. But, by applying machine learning algorithms to decision-making processes, Decision Intelligence helps create strong decision-making models that are applicable to a large variety of business processes and functions.
The limitation of traditional AI models in delivering accurate decision-making results is that they are designed to fit the data that the business already has. This bottom-up process leads to data scientists concentrating more on data-related problems rather than focusing on business outcomes. Little wonder then that, despite an average of $75 million being spent by Fortune 500 companies on AI initiatives, just 26% of them are actually put into regular use.
Decision Intelligence models work on a contrarian approach to traditional ones. They operate with business outcomes in mind — not the data available. Decision Intelligence combines ML, AI, and Natural Language queries to make outcomes more comprehensive and effective. By adopting an outcome-based approach, prescriptive and descriptive solutions can be built that derive the most value from AI. When the entire decision-making process is driven by these Decision Intelligence models, the commercial benefits are realized by every part of the organization.
Decision Intelligence Delivers Enterprise-Wide Benefits
Incorporating Decision Intelligence into your operations delivers benefits that are felt by every part of your business. These benefits include:
- Faster Decision-Making:
Almost every decision has multiple stakeholders. By making all factors transparently available, all the concerned parties have access to all the available data and predicted outcomes, making decision-making quicker and more accurate.
- Data-Driven Decisions Eliminate Biases:
Every human process data differently. When misread, these biases can impact decisions and lead to false assumptions. Using Decision Intelligence models, outcomes can be predicted based on all the data that a business has, eliminating the chance of human error.
- Solving Multiple Problems:
Problems, as they say, never come in one. Similarly, decisions taken by one part of your operations have a cascading effect on other departments or markets. Decision Intelligence uses complex algorithms that highlight how decisions affect outcomes, giving you optimum choices that solve problems in a holistic, enterprise-wide way, keeping growth and objectives in mind.
Decision Intelligence: One Technology, Many Use Cases
Decision Intelligence tools are effective across a multitude of business applications and industry sectors. Here are some examples of how various industries are using Decision Intelligence to power their growth strategies:
- Optimizing Sales:
Decision Intelligence can get the most out of your sales teams. By identifying data on prospects, markets, and potential risks, Decision Intelligence can help them focus on priority customers, predict sales trends, and enable them to forecast sales to a high degree of accuracy.
- Improving customer satisfaction:
Decision Intelligence-based recommendation engines use context to make customer purchases easier. By linking their purchases with historical data, these models can intuitively offer customers more choices and encourage them to purchase more per visit, thus increasing their lifetime value.
- Making pricing decisions agile:
Transaction-heavy industries need agility in pricing. Automated Decision Intelligence tools can predictively recognize trends and adjust pricing based on data thresholds to ensure that your business sells the most at the best price, maximizing its profitability.
- Identifying talent:
HR teams can benefit from Decision Intelligence at the hiring and evaluation stages by correlating skills, abilities, and experience with performance benchmarks. This, in turn, helps them make informed decisions with a high degree of transparency, maximising employee satisfaction and productivity.
- Making retail management efficient:
With multiple products, SKUs and regional peculiarities, retail operations are complex. Data Intelligence uses real-time information from stores to ensure that stocking and branding decisions can be made quickly and accurately.
Incorporating Decision Intelligence into the Solutions Architecture
CTOs and solutions architects need to keep four critical things in mind when incorporating a Decision Intelligence into their existing infrastructure:
- Focus on objectives:
Forget the data available for a bit. Instead, finalize a business objective and stick to it. Visualize short sprints with end-user satisfaction in mind and see if the solution delivers the objective. This approach helps technical teams change their way of thinking to an objective-driven one.
- Visualize future integration:
By focusing on objectives, solution architects need to keep the solution open to the possibility of new data sets arising in the future. By keeping the solution simple and ready to integrate new data as it comes in, your Data Intelligence platform becomes future-proof and ready to deliver answers to any new business opportunity or problem that may come along.
- Keep it agile:
As a follow-up to the above point, the solution needs to have flexibility built in. As business needs change, the solution should be open enough to accommodate them. This needs flexible models with as few fixed rules as possible.
- Think global:
Decision Intelligence doesn’t work in silos. Any effective Decision Intelligence model should factor in the ripple effect that a decision — macro or micro — has on your entire enterprise. By tracking dependencies, the solution should be able to learn and adapt to new circumstances arising anywhere where your business operates.
Machine learning and artificial intelligence are niche technologies, and companies have started thinking about or utilizing these technologies aggressively as part of their digital transformation journey. These advancements have changed the demand curve for data scientists, machine learning, and artificial intelligence technologists. Artificial intelligence-driven digital solutions require cross-collaboration between engineers, architects, and data scientists, and this is where a new framework, “AI for you, me, and everyone,” has been introduced.
To Sum Up
Decision Intelligence is a powerful means for modern businesses to take their Artificial Intelligence journey to the next level. When used judiciously, it helps you make accurate, future-proof decisions and maximize customer and employee satisfaction, letting you achieve your business objectives with the least margin of error.