“How quickly can we act on this data?”
It’s a question that once defined the limits of business intelligence (BI) and advanced analytics teams. Only a decade ago, many executives found themselves at the mercy of rigid data teams, delayed analyses, and insights delivered just after they became relevant.
Most of the problems faced were not due to a lack of data, but rather to the overwhelming amount of unstructured, unrelatable data that required specialists to sift through on fishing expeditions.
Data was everywhere, but intelligence was scarce
Time was tight, and catching up often felt out of reach as every analytics initiative seemed more like a postmortem than a forecast. It was like having multiple teams with great insights, but each spoke a different language and could not understand the others. You had to look at each in a silo, translate, and combine before you could see any patterns of worth.
But those days are over.
Mature BI data has landed
The barriers to leveraging intelligence have all but evaporated with modern advancements in data processing and artificial intelligence (AI). SaaS platforms process billions of structured transactions, creating an enormous data store needed to train AI. This connection of data and intelligence has enabled new ways to drive optimizations and cost savings in the warehouse.
Modern tools—driven by subject-specific data, automation, AI, and sophisticated workflows—have transformed how businesses take action. Data is no longer something specialized teams need to mine for; it’s already waiting, ready to guide decisions at precisely the moment they matter most.
Companies are starting to separate themselves from the AI pack—how are they doing it? By leveraging the power of Large Language Models (LLMs) and providing the data source and context that helps the LLM become a Subject Matter Expert for your specific goals. Think about how Google is using YouTube to refine its video-generating software and make faster, more impactful advancements than others. It’s because of the data entitlements they have access to.
So, why wait on the sidelines? You have a “YouTube” to power your data, and it is your planning and execution data that helps you understand when and where you can make the most impact from the patterns you have seen in the past.
From data science to decision science: a new era of accessibility
Not long ago, the term “citizen data scientist” emerged to describe a profound shift: placing the power of BI in the hands of everyday professionals rather than specialists. Tools like Tableau, Power BI, and early machine learning platforms promised to move insights out of the realm of complex coding and into user-friendly dashboards.
Back then, the promise felt revolutionary
And it was for its time. While the barrier to data visualization decreased significantly, the grunt work of mining, normalization, and harmonization remained a persistent challenge. It also did not provide any understanding of why; it simply showed what happened through various KPIs.
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Tools still couldn’t entirely strip out the manual friction. Businesses continued to experience bottlenecks due to schema misunderstandings, clunky data formats, and processes that couldn’t keep up with changing assortments, seasonality, and supply chain disruptions.
AI is rewriting that story
The focus of AI in the supply chain is no longer just on gaining access to information—it’s ensuring that the correct data reaches you, in context, at precisely the moment you need it. It’s focusing on insights, outcomes, and prescriptions at the speed of business. We’ve moved the narrative from “what happened?” to “how should we?” It also helps with clarity, where are we doing well, and where should I focus my attention to benefit us the most?
How Leaders Are Driving Breakthrough ROI With AI. While others debate AI’s potential, growth-focused leaders are already banking real returns. This comprehensive report shows 46% of organizations have already implemented AI in their supply chains.
A helpful comparison? ChatGPT
Think about how simply typing a natural question in ChatGPT returns entire paragraphs of actionable text. That’s intelligence democratization at work—and AI is now applying that same principle more deeply across industries. But there are requirements for working with AI, and one is providing the proper context for the AI to assist you.
Take that GPT suggestion we started with. The actions seem very direct and impactful. But if you examine the actions closely, you’ll see it is too general to really provide the benefit you need past surface improvements. It lacks context for your business and the greater market to truly help you refine your processes.
For supply chain professionals, this means data is accessible but actual intelligence requires data context to succeed.
Bringing intelligence to life
In supply chain operations, as in most complex businesses, the challenge now isn’t having data—it’s connecting it with clarity and your business goals. Traditional business analytics could tell you what had happened in neat rows and columns. We have gone beyond that, and it is now about answering more complex questions:
- Why did this happen?
- AI uses historical execution data to uncover the root causes of slowdowns, bottlenecks, or surging demand.
- When will it matter most?
- Predictive intelligence forecasts windows of urgency before they arise, and platform providers can use market trends to make more accurate predictions by analyzing their customers’ activity.
- How can I take better action now?
- With insights tuned into your business priorities, your decisions are directed to the ones that matter most, using market baselines that show you real opportunities based on similar businesses.
Request a personalized demo of Deposco’s Supply Chain Intelligence (SCI) solutions to unlock insights, outcomes, and prescriptions at the speed of business.
Deposco’s SCI solution: your silent helper
Deposco’s AI-enabled SCI solutions bring a high level of sophistication to the supply chain. Using our billions of transactions, historical planning, and execution activities processed through our platform, we benchmark businesses against others with similar businesses. This gives our AI models the context needed to provide clear improvement direction with measurable bottom-line impact.
Think of it like a healthcare provider. By using patterns from thousands of patients, a physician can identify where someone is healthy, where they may be at risk, and which interventions will deliver the best outcomes. Deposco’s SCI works the same way for your supply chain. It identifies where your business is in great shape, where there are risks, and creates a tailored “treatment plan” to optimize results.
Forecasting, for example, becomes less about dissecting past trends and more about interpreting signals across your operations. Instead of simply spotting that shipping costs are rising, SCI can pinpoint whether labor performance, inventory positioning, or supplier delays are the actual underlying issue, and then recommend the right corrective actions. This could mean reallocating inventory ahead of a demand spike, shifting orders to cover a supplier delay, or right-sizing labor to reduce excess cost.
The best part is that this intelligence doesn’t require a specialist to interpret it. SCI transforms raw data into actionable, easy-to-understand insights. AI’s evolution is about simplicity as much as it is advancement. Deposco’s SCI tools allow modern supply chain leaders to focus on action, not drawn-out analytics. It provides confidence that they have the right prescription for healthier, more profitable operations.
Removing the barriers—and excuses—to AI adoption
For some businesses still pondering the leap into advanced intelligence tools, hesitation stems from understandable concerns. Whether it’s skepticism about AI’s real value or a misplaced comfort with inefficient legacy WMS systems, these barriers are holding you back from the benefits already within reach.
Consider these misconceptions about AI:
- AI is too complex or requires a team to understand, develop, and manage.
- Implementing new tools will disrupt existing workflows.
- Intelligence is a “nice to have,” not a necessity.
But these assumptions, as countless businesses adopting AI-driven systems have found, couldn’t be farther from the truth. Partnering with the right provider simplifies the process and removes the adoption barriers. Businesses are quickly finding the competitive advantages that AI is driving in the supply chain. Deposco Intelligence solutions integrate smoothly within existing systems, enhancing—not overhauling—your workflows. The payoff is immediate, measurable, and human-enabling.
What are you waiting for?
Deposco helps leaders across industries solve forecasting challenges, modernize operations, and scale their supply chain actions with precision.
For those standing on the ledge of AI adoption, here’s the reality:
The question is no longer if you can access data; it’s how quickly you’re willing to act on the insights that drive organizational success.
Waiting for answers is legacy.