In today’s data-rich environment, traditional decision-making methods often fall short against the tide of information. While human intuition is invaluable, it’s not enough to meet the demands of modern business challenges. So, why is it so difficult to bridge the gap between vast data sets and actionable insights in AI-driven decision-making?
Data is complex
Real-world outcomes are shaped by a multitude of factors, many of which are not captured as data points. Despite this, machine learning algorithms are expected to fully model these complex real-world scenarios using fragmented data, and the process is rife with challenges.
From limited data availability to data complexity, or just downright noisy data – in various instances, data can be a difficult problem to solve. To make matters worse, a lack of domain expertise can further complicate accurate data interpretation, making data-driven decision-making a more daunting endeavor.
For an accurate business decision engine, the system should leverage both domain knowledge as well as machine-powered decision-making based on robust historical data. This is where Altimetrik’s Business Decision Engine steps in, turning this data-haze into clarity.
Bridging data gaps with Altimetrik’s Business Decision Engine
Altimetrik’s Business Decision Engine (BDE) is a holistic AI-powered solution that aims to alleviate the most pressing challenges with data-driven business decision-making. It accounts for variables that influence real-world outcomes, by combining discriminative, and generative AI, ML, domain information, and human intelligence.
Man and Machine: creating something greater than the sum of the parts
Altimetrik’s BDE works at two levels. It first builds a fully automated solution leveraging existing data. On the next level, it adopts a semi-automated approach, by injecting domain information and human intelligence which was not present in the data initially. The domain experts help fine-tune BDE for better results.
Consider a hospital trying to optimize operations: Initially, the system may identify extended patient wait times and suggest increasing staffing levels. However, domain experts recognize the issue stems from bottlenecks in specialized equipment availability during specific shifts. By integrating this nuanced understanding, the system would then recommend reallocating equipment and providing targeted staff training. This human intervention mitigates unnecessary red flags, thus maintaining focus on actual areas of concern.
Low data volume? No problem.
Another issue businesses must contend with is the inadequacy of quality data. To that end, when using other solutions, they run into the dreaded ‘not enough rows of data’ error. With BDE, we wanted to ensure this was not even a consideration for our customers. Therefore, it offers accurate insights with as little as150 rows of data (while competitors may require three to four times as many). And for the instances where there still isn’t enough data, our Synthetic Data Generator (SDG) steps in to create robust, quality datasets based on pre-existing patterns. This enables the system to now account for scenarios beyond the original data’s scope.
This translates to a model that is trained with both machine and human intelligence, resulting in business decisions that are more comprehensive, thorough, and domain-specific.
It addresses the four pressure points mentioned below:
Predicts KPIs: Leveraging a holistic AI suite, BDE is capable of predicting/forecasting the KPIs laid out, accurately, even with the minimum amount of available data. This not only enhances proactive strategy formulation but also enables businesses to stay ahead of market trends and capitalize on emerging opportunities with confidence.
‘What-If?’ analysis: BDE offers a deep view of a particular influencer’s impact, enabling accurate what-if analysis and more informed decision-making. This helps business leaders simulate various scenarios and evaluate potential outcomes. This empowers businesses to step beyond educated guesses, into a world of calculated possibilities.
Optimizes workflows: With BDE, you can derive optimized values for each influencer, which can result in either maximizing or minimizing the KPI. This streamlined approach boosts operational efficiency, fine-tunes resource allocation, and ensures that every decision contributes to achieving comprehensive business objectives effectively.
Identifies Key Contributors: BDE allows the selection of true influencers from a large pool of influencer data effectively, ensuring that businesses focus on the most impactful factors. This helps marketers in the team optimize their marketing strategies while improving brand visibility and engagement, driving tangible business results in a competitive landscape.
Consider a retailer evaluating whether a weekend discount will boost sales or cannibalize full-price purchases. BDE can analyze the impact on sales volume, profit margin, and full-price sales. It will reveal not just if the discount increases sales volume, but also by how much. Similarly, it will show the direction and extent to which the discount might affect full-price sales and profit margin.
Where does BDE thrive?
BDE works across a myriad of domains. Be it healthcare, where it can predict patient footfall, or finance, where it forecasts revenue and predicts redemption, or retail, where it helps with demand forecasting, price optimization, etc. An appropriate analogy would be that of a Swiss army knife; equipped with precise tools specifically designed to tackle the unique challenges of each domain.
In a nutshell, modern business is demanding, and seemingly minor details within the value chain can significantly impact profitability and sustainability. Informed, data-backed decisions are the ultimate differentiator. And with Business Decision Engine (BDE), we’re transforming how businesses—regardless of the complexity, volume, and depth of data, make informed decisions.
