Overnight, ChatGPT and generative AI became a topic of conversation at nearly every board room and dinner table. AI is no longer an aspirational technology; it’s here now. And with 3-4x more data than companies in other industries, manufacturers have the greatest potential to mitigate risk, uncover hidden patterns, and unlock new opportunities with the power of advanced analytics and Artificial Intelligence. Here’s a look at what you can gain when you leverage data to transform your business and practical steps for getting started.
Data as an Asset: The shift from rear-view mirror reporting to real-time intelligence
Many of our clients have grown significantly over the years, adding complexity to their global operations. Cross-functional teams spend hundreds of hours each week manually organizing and prioritizing activities – be it production/fulfillment planning, demand forecasting, procurement, logistics, sales, or finance. This unfortunately leaves very little time or resources to negotiate pricing and optimize operational decisions that impact the bottom line.
Such was the case for one automotive assembly plant operating under a multinational manufacturer. Through a Data Value Assessment, the plant discovered the procurement team spent only 19% of their time on activities directly related to price negotiations. Inefficient activities like transferring data and tracking down documents consumed the other 58% of the time. By adopting a modern data platform and eliminating manual processes, the automotive plant can expect to save 600 to 800 hours per week and cut raw material costs by millions annually.
Another manufacturer we partnered with discovered they were spending 60% of their end-to-end cycle time capturing, exporting, consolidating, and validating data. With this laborious process, reporting and insights were only available once a week. As a result, the manufacturer was spending hundreds of hours on a repetitive process ripe for automation and real-time insights.
With plant floor automation, digital collaboration with suppliers, and customer buying journeys, the volume of data grows exponentially each day. By analyzing this untapped data, you can increase visibility, reduce costs, mitigate risks, uncover new opportunities, and even increase company valuation. But creating yet another “weekly report” just won’t do. You must instead keep a continuous pulse on customer demand by leveraging all available signals.
It all starts with a more accurate demand signal
Once upon a time, manufacturers could plan procurement, production, and logistics with basic back-of-the-napkin assumptions of growth and seasonality. But those days are gone! In this new era of constant market shifts, it’s about spotting trends, predicting risks and opportunities, and taking swift action. To do this, you must comprehensively and continuously analyze transactional data like customer orders, inventory levels, and supply chain movements. And to maximize demand forecast accuracy, going beyond transactions to include data from partners and suppliers is critical.
Given contextual market changes, it may be appropriate to give more weight to the past 12 weeks of a demand signal versus the past 12 months (despite historical seasonality) for a stronger indicator of what comes next. Developing a way to test and swap forecasting models to improve accuracy and adjust on-the-fly is also critical. This will help you avoid every manufacturer’s nightmare: aging inventory sitting on shelves, endless expedites to meet demand you didn’t plan for, eroding margins, and cancelled orders.
Leveraging generative AI to improve sourcing and gross margins
When examining operational processes across multiple divisions, we frequently find siloed procurement eroding margins. By independently procuring parts by division (often with some of the same suppliers), manufacturers miss out on volume negotiations and a holistic view of available inventory and supplier performance.
Instead of simply submitting orders to your suppliers, proactively collaborate with them on an intelligent demand forecast, available supplier capacity, upstream constraints, and real-time order status/risk mitigation. This collaboration will help both of you become more efficient and profitable.
One example we’ve seen is a global computer electronics manufacturer that can now plan production in hours versus days. The company owns component inventory for just a few hours before shipping it out to customers for 60% less on-hand inventory while maintaining an industry-leading order fill rate. If the manufacturer senses a demand shift, they can replan procurement, production, workforce, and their whole value chain inside of a day.
When you analyze data across traditional internal silos, partners, and customers, trends emerge that provide valuable insights. Perhaps more importantly, you can quickly make adjustments that will help you optimally serve your customers while managing the bottom line. Data isn’t just a byproduct of manufacturing; it’s an asset in its own right. And when combined across functional siloed areas, it creates multiplicative value, enhancing your company’s worth and delivering a competitive advantage.
What are the hurdles to surfacing and tapping into the value of data?
However, despite its immense potential, most manufacturers analyze just 12% of their data, and only a quarter have achieved a data-driven culture. More than half are unable to acquire the expertise necessary to take full advantage of the AI revolution. So, why do so many manufacturers struggle to harness the untapped value of data?
One major obstacle to unlocking the value of data in manufacturing is its sheer volume and complexity. With an overwhelming amount of data coming from sensors, machines, robots, supplier interactions, digital customer interactions, and multiple ERP instances, extracting meaningful insights can be a daunting task. For global organizations, consolidating and harmonizing data across multiple departments and locations can seem impossible, especially during times of expansion or acquisition.
Reliance on manual processes
51% of executives cite business or process challenges among their chief constraints to using AI. Unfortunately, relying on manual processes not only limits the ability to extract actionable insights; it also creates mistrust. If there’s no single source of truth, or if one wrong keystroke can skew a whole report, leaders have a tough time trusting the numbers.
Delaying focus on AI until you “get the foundation in place”
Creating an AI strategy upfront will help drive the urgency and investments you need to build a scalable, intelligent foundation. It will also drive efforts to establish governance and improve data quality – and therefore better decision-making. A single initiative won’t typically justify the foundational investments needed. But once you spread this investment across a multitude of predictive scenarios tied to quantifiable business outcomes, it becomes a no-brainer.
How to get started
Define your strategy and use cases
So, in practical terms how do you take a sprawl of enterprise data and turn it into something insightful? Start by developing your broader data strategy. Define the business questions that you need help answering and trends need to surface. Ask yourself: If you had a specific piece of information, if you could predict the future, what would you change, and how would that impact your business?
Consolidate and curate your enterprise data into a unified intelligent platform
With AI moving so fast, many manufacturers are moving away from hiring large teams for traditional data warehouse projects that can run for 18 or more months. Instead, they turn to a seasoned industry partner and intelligent data platforms to jump start their cloud analytics and AI capabilities.
The first piece of advice we give our clients is to avoid the common mistake of trying to create a data foundation and solution for one specific scenario. A unified data foundation, curated for real-time intelligence, will serve you exponentially as you scale your business and uncover new trends.
To build the right foundation for real-time analytics and AI, map out where all your data is and begin to define how it can drive value based on industry standards and your unique business model. You should then focus on consolidating this data to improve visibility and grant widespread access. By equipping business leaders and subject matter experts with self-service business intelligence, you foster a data-driven culture and drive faster, smarter decisions. Next, look at the data that is valuable but not yet available to you (market, supplier, customer data), and build a plan to begin adding that to your foundation.
To support confident and timely decision-making, you must maintain data integrity and consistency. Be sure to leverage industry best practices in establishing clear data definitions, quality control measures, and data governance.
Leverage a third-party data platform for fast time-to-value
Modern data platforms should also be scalable and extensible in the event of future acquisitions and the introduction of new systems. To address the growing labor shortage, up to half of manufacturers are looking to AI and machine learning to fill in the gaps. A pre-built data foundation like MCA Connect Inspire Platform™ can help you lay the scalable foundation that’s optimized for real-time manufacturing intelligence in a matter of weeks.*
Embrace the transformation
As AI and machine learning continue to grow, the potential for manufacturing sector is enormous. By embracing generative AI and harnessing the power of data, manufacturers like you can unlock untapped potential to improve fill rate, product quality, and overall efficiency, all while delighting customers.
In this new era of constant market shifts and generative AI, it’s critical to harness the power of data to drive tangible business outcomes. With more than two decades helping manufacturers better leverage their data for strategic advantage, we can accelerate your data and AI journey. For many of our clients, Microsoft funding is available to help you get started.
*MCA Connect Inspire Platform™ integrates out-of-the-box with Microsoft Dynamics 365, Power Platform, and other 3rd party applications
Vice President – Manufacturing Intelligence & Advanced Analytics
Most companies analyze just 12% of their data and only a quarter have achieved a data-driven culture. However, the data landscape is changing, and more companies are uncovering new insights with modern technology. In this episode, Melinda Carlson and James Roberts discuss how leading manufacturers are leveraging their data to get ahead, plus practical tips for getting started.
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