The Business Use of Data
In modern business media, we often see and hear the term ‘data-driven business’, and for good reason. Companies that collect and analyze data in all aspects of their business quickly identify opportunities for improvement. The use of data analytics helps businesses trim operating costs, improve service delivery and product management, streamline order processing and logistics, and boost advertising effectiveness. All of these process improvements lead to increased demand and increased profit margins, and free resources to help meet demand growth.
Our ability to collect data continues to improve, in terms of scope, volume, quality, and timeliness. However, the data we collect is useless, unless we can efficiently process it in ways that provide insight into how we can improve our business and operational workflow streams. Data analytics provides a great mechanism for helping us leverage our increased ability to collect data. We can use data analytics in both the operations and the marketing arenas.
The remainder of this article highlights some key ways that data analytics can help us improve our business workflow and profits. We will show you data collection and analysis can inform your business and drive your distribution business growth.
Trim Operating Costs
Which aspects of business and operational workflow contribute to the operating costs of a distribution business? Answer: Every one of them contributes to cost, not only individually, but also in relation to the overall workflow. Each element of the production and distribution business discussed below provides an opportunity to trim operating costs, thereby increasing profits.
Enhance Production Efficiency
Although this article focuses on the distribution business, we also address how we can use data to improve production efficiency. We do this because many companies combine both production and distribution into a single business and because production efficiency directly affects distribution efficiency.
For the sake of simplicity, consider a production process with each stage in series, where each stage ends before the next stage starts. Without changing this workflow, we can improve operational efficiencies by focusing on each operational step. For example, we can work to maintain or improve equipment uptime, ensure continuous availability of feedstocks, increase production capacity by upgrading equipment, etc. Focusing on individual work streams allows us to identify operational deficiencies. We can use this information to fine tune each stage and reduce the incidence of operational slowdowns that cause one stage to wait on another stage. Unfortunately, the cumulative cost of human resources prohibits continuous monitoring at each stage by humans.
Using modern technology, however, we can automate monitoring for some or all stages of production. We can design the system to provide alerts when any element in the system lags performance targets. We can even automate response to alerts, taking human response time out of the equation. For example, automated systems can generate orders for supplies feeding the line based on inventory levels and approved production orders.
Applying data analytics, we can improve the process even further. In some circumstances, we can use data analytics to project potential lags or slowdowns even before they occur and automate responses to ensure the production slowdown never happens.
When we apply a similar methodology to the distribution aspect of the business, we realize similar results.
To achieve these profit-enhancing benefits, we need to understand where data collection applies and how to collect it. Be on the lookout for greater coverage on this topic (data collection and analysis techniques) in a future CIS blog post.
Improve Product Quality
Defective products slow down the entire business supply chain, including distribution. When the customer rejects products, the supplier absorbs the cost of unplanned logistics and accounting corrections. Conversely, when we produce products to specification and deliver without damage, these inefficiencies and unplanned costs go away.
The collection and analysis of data at key points in the production through the distribution chain can help rid the system of these unplanned events and resulting profit erosion. In the production process, strategic sensor placement allows continuous measurement of critical aspects of the product that contribute to the quality, for example, dimensional data.
Improve Delivery Service
Data analytics can help you define and improve weaknesses in the delivery service. Predictive analytics helps with forecasting customer demand, allowing your business to prepare for peak production periods by increasing inventory, gearing up production lines for greater activity, etc. Making adjustments proactively can result in the ability to commit to delivery of products or services that your business would otherwise not be prepared to deliver from a when challenged with minimal advance notice.
Improve Inventory and Product Management
With automated inventory control, your company can more effectively manage all phases of product manufacture and delivery. For example, bar code scanning, coupled with inventory management software, automatically updates supply inventory count on receipt of supplies. During production, the software automatically decreases supply inventory and adjusts product inventory based on consumption. Similarly, as products ship to the customer, the system automatically adjusts product inventory.
Using this process and quality management software, your business maintains accurate inventory count and provides reliable data to business functions such as invoicing, supply purchasing, etc. This process removes human error due to manual data input, miscounts, etc. Consequently, your business enjoys a significant reduction in the time required for inventory reconciliation.
Streamline Order Processing and Logistics
Improved inventory management enables streamlining processing of sales and production orders, warehouse management, and shipping operations. For example, you can automate notifications or even automatic ordering of supplies when supply inventory reaches low thresholds. Using data analytics, you can predict market fluctuations and automatically update supply inventory thresholds. These processes can significantly reduce the overall cost of production and increase profit margins. Additionally, these processes and tools can reduce unit production time, allowing you to produce more products within facility constraints, and continue to grow your production and delivery business.
Marketing and Sales
In addition to the operational benefits described above, data analytics can help you better understand and predict evolving market conditions and find missing sales opportunities.
Perform Market Assessment
Analyzing sales data helps your business understand and predict market trends and fluctuations, hence identify opportunities to capture greater market share. Data analytics can help you identify seasonal effects and forecast trends with greater accuracy. This leads your ability to respond to market changes very early in the cycle. Both internal and external sales data provide valuable information for this exercise.
Additionally, market assessments can help your company identify opportunities where your company has the resources (or can readily hire or develop resources) to fill gaps in supply and demand.
While data analytics offers a competitive advantage, a business also must have information that data cannot always provide. Production and distribution businesses also need direct customer feedback to help you understand what your customer wants from a supplier. Such communication serves to enlighten both suppliers and customers. Digitization and analysis of customer feedback information provide opportunities to learn more about your entire supply chain.
Boost Advertising Effectiveness
Data analysis, based on historical market conditions and sales trends, provides valuable information to assist with the development of effective advertising strategies for the future. You can learn which sales and marketing tactics have worked best for specific market conditions, using internal and external sales and marketing data. Comparing this information with your company’s marketing and sales techniques, as well as sales history, enables you to identify missed sales opportunities. These insights, combined with predictive analytics, can help you formulate strategies to act timely on historically missed opportunities.
This blog post was written in collaboration with SalesPad. Learn more about SalesPad at salespad.net.