ARTICLE
1 November 2024

How Business Intelligence Empowers Manufacturers And Distributors

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Kaufman Rossin

Contributor

Kaufman Rossin, one of the top CPA and advisory firms in the U.S., has guided businesses and their leaders for more than six decades. 600+ employees deliver traditional audit, tax, and accounting, plus business consulting, risk advisory and forensic advisory services. Affiliates offer wealth, insurance, and fund administration. We’ve earned many awards, but we’re most proud of our Best of Accounting®️ Award for superior client service for four years running, because it’s based on ratings from more than 1,000 of our clients.
As companies increasingly rely on Business Intelligence (BI) for real-time insights and decision-making, investing in the right technology and professional expertise...
United States Corporate/Commercial Law

As companies increasingly rely on Business Intelligence (BI) for real-time insights and decision-making, investing in the right technology and professional expertise will be crucial to stay competitive.

The manufacturing and distribution sectors are grappling with a rapidly evolving landscape marked by rising freight and materials costs, supply chain disruptions and increasing competition from new entrants as well as established online platforms such as Amazon. Companies are under constant pressure to manage inventory effectively, mitigate stockout risks, control unit costs and meet growing customer expectations. Adding to this, many manufacturers and distributors face a persistent challenge to manage the complexity of their supply chains.

Business intelligence (BI) offers the opportunity for data-driven decision-making that can help meet these challenges head-on. BI involves collecting, integrating, analyzing and presenting business data to surface key information, trends and issues. Essentially, BI transforms data into actionable insights. It can enhance operations, optimize processes, reduce costs and drive revenue growth.

Transforming Data into Insights

A BI platform unifies data from multiple sources into one or more intuitive dashboards, offering stakeholders a clear and actionable view of the vast amounts of information available. For example, a BI dashboard might visually track progress and trends related to key performance indicators, enabling stakeholders to make adjustments based on real-time data.

An effective BI dashboard would be customized for the company's and user's needs. A manufacturing or distribution company might use BI to monitor and manage the end-to-end supply chain, from production to delivery, to maximize the chances that products meet targets and commitments. Similarly, BI tools can enhance demand forecasting and inventory planning.

BI can help drive performance, adapt quickly to changes, and ultimately deliver a competitive advantage through insights. Let's consider some BI use cases for the manufacturing and distribution sectors.

Enhancing Operational Efficiency

BI tools provide insights into key operations and risks, enabling companies to optimize processes and enhance responsiveness. This can be applied in many ways:

  • Supply chain visibility – Companies can monitor the status of products in real time, from production through delivery. By surfacing potential delays or other issues, companies can proactively address — and hopefully prevent — disruptions.
  • Demand and inventory planning – Combining internal and external data enables more accurate demand forecasting and monitoring of sales velocity trends, which allows for more effective planning for production and orders. This allows businesses to better manage inventory levels and minimize stockout risks. It can also significantly reduce the labor time required for these activities.
  • Supplier and vendor performance monitoring – BI enables real-time tracking of vendor and supplier key performance indicators (KPIs) against service-level agreements. This can improve delivery efficiency while strengthening supplier relationships.
  • Product quality and compliance optimization – Trends in returns, complaints and product defects can be viewed in an understandable, real-time way to make rapid adjustments.
  • Optimization of sustainability – BI is an excellent tool for identifying inefficiencies and waste in the supply chain, and it can be a key component of a sustainability program. It can also report progress on KPIs related to regulatory standards and targets.
  • Maintenance prediction – BI can track equipment performance and age against predicted longevity and maintenance requirements, enabling companies to minimize equipment failures and downtime.

Reducing Costs and Improving Profitability

Companies that use business intelligence generally find they're also able to better identify hidden inefficiencies and cost drivers across operations. BI's holistic data view is particularly useful to manage three areas:

  • Unit economics – More detailed insights into product-level costs and profit margins support both macro and micro decision-making, which can significantly affect overall profitability.
  • Purchase orders – BI excels at surfacing information, including within purchase orders. This enables more accurate understanding and management of the costs of goods sold and cash flow.
  • Supply chain costs – Accurate visibility into all supply chain costs — including freight, storage and delivery — facilitates better planning for shipment and inventory. These insights also support better contract management with partners.

Driving Revenue Growth

Finally, BI helps companies optimize current revenue and identify new streams of revenue through market analysis and customer-behavior insights. With this, BI can significantly inform several key areas:

  • Managing customer expectations – By leveraging real-time insights into order status early in the process, companies can better manage customer expectations on orders and delivery times.
  • Improving the customer experience – BI brings together large amounts of data from disparate sources. Companies can use customer data to better understand each customer's needs, expectations, and priorities, enabling more personalized customer experiences.
  • Improving existing products and developing new offerings – End-consumer insights can be mined to refine product offerings based on their pain points, needs and product usage, driving innovation.

Effective BI Implementation: Where to Start

Successful BI implementation requires more than just adopting the technology. Strategic alignment within the organization around the value of BI and priorities for using it are key. So is tapping into inside or outside expertise to configure the system and individual dashboards to surface the most actionable, relevant information.

Here are seven key steps to an effective BI implementation:

  1. Set clear objectives around the business value that BI needs to drive.
  2. Build a road map for execution, keeping the objectives in mind.
  3. Identify the internal and external team for development, including who will fill the key roles of business strategist, data analyst, data scientist and user experience/user interface expert.
  4. Identify existing data and data sources and inspect their quality. Ascertain how to feed only high-quality data into the BI system.
  5. Build a list of potential BI uses cases, with indicators for each one's potential ROI and estimated difficulty.
  6. Select a small number of use cases on which to focus early development. These should be high-ROI and not too big to tackle early.
  7. Identify the needs of the key roles and functions in those use cases and design a user-centric experience that provides the insights they really need, when and how they need them.

Build a Culture of Data-Driven Decision-Making

BI is not a "build it and they will come" technology. It's a new way of doing business, and it needs to be embedded into the company's DNA. Unless you cultivate a companywide culture of data-driven decision-making, that will not happen.

Less digitally mature organizations may want to start with basic BI solutions that can help employees first understand their data to make more informed decisions without overwhelming them. More digitally mature organizations can leverage advanced AI-driven BI solutions, including predictive modeling, optimization modeling and scenario planning. Scale up both the sophistication of the solution and the breadth of use cases it's applied to.

The Future of BI in Manufacturing and Distribution

The role of BI in manufacturing and distribution is set to grow, particularly with the integration of AI and advanced analytics. According to a forecast by ABI Research, industrial enterprises worldwide are projected to generate a total of 4.4 Zettabytes (ZB) of data by 2030 (a significant increase from 1.9 Petabytes in 2023), highlighting the exponential growth of data in the manufacturing sector.

Future trends include more sophisticated predictive models and the use of generative AI to optimize customer service, marketing and sales, and strategic planning. Remember, though, that investing in BI is not just about technology — it's about equipping your organization with the insights needed to thrive in today's complex business landscape.

As companies increasingly rely on BI for real-time insights and decision-making, investing in the right technology and professional expertise will be crucial to stay competitive. The game-changing value of turning data into actionable insights is not something most manufacturers or distributors can afford to ignore.

Read the full article on Supply & Demand Chain Executive.

The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.

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