As companies grow in size and complexity, providing actionable, analytical information to senior management has become increasingly difficult. No one system provides more than 10% of the data senior management needs. Key data such as plans and history often exist in spreadsheets outside the information systems. Systems such as the telephone phone switches (ACD) have valuable productivity and service data, but management usually doesn’t have access to it. Reports from commercial systems by software companies often leave the user wanting a lot more.
Today’s Biggest Business Information Problem
Multichannel companies not only have multiple channels for dealing with customers; by their very nature, these companies often have multiple systems, with numerous—and differing—occurrences of key data and metrics. Depending on the database design and the age of the information systems, there may even be multiple occurrences of key data within a single system. This problem is actually worse in companies with large scale multichannel “systems”—because in reality, these are multiple individual applications. Many companies have grown up selecting best-of-breed systems, and since no one vendor in the marketplace today can provide more than two of the best-of-breed systems needed, these have disparate databases and designs. With separate systems for order management, fulfillment, call center ACD switches, marketing, product information, inventory, finance and e-commerce, we have created silos of information across the enterprise. ERP system proponents may say, “this is what we have been trying to tell you for years,” but the reality is that most ERP systems available to the direct marketplace don’t provide specialized direct, retail or warehouse management functions that are as good as best-of-breed.
Solving Data Problems With BI Solutions
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In moderate to large companies the multichannel transaction systems consist of a significant number of information systems and databases. Here are some typical examples:
- Catalog/e-commerce order management, marketing and merchandising system (OMS)
- Warehouse management system (WMS) if not part of the OMS
- Telephone switch software (ACD)
- Financial applications (accounts payable, accounts receivable, general ledger, etc.)
- Specialized standalone merchandise planning and forecasting system
- POS and retail merchandising system for brick and mortar stores
- E-commerce site and web analytics systems
- Internally developed systems using Access or other small data bases
- And there are hundreds to thousands of spreadsheets (including sales plans and history) extracting more tailored info for management
These best-of-breed systems are not designed with the same “look and feel” or navigation, and their database structures can span 25 years of systems development with Oracle, DB2, Access, COBOL, Java, C++ and .net. Management often has to get its information by having business analysts or department managers pulling data from these disparate “silos” into spreadsheets, Access databases or by using OLAP tools—and that’s a big problem. There are delays in getting the data, because much of it cannot be online, real time; there is considerable cost in massaging the data; a continual need to keep it updated; inevitable manual errors; and lack of the ability to add any sophisticated analysis to it. Perhaps worst of all, data often doesn’t reconcile from one information system to another, and therefore there isn’t a “single version of the truth.” On which version of the data should you base your decisions?
There Is A Solution
Business intelligence software and services now exist which can open up systems and standardize data across systems in the enterprise, opening up tremendous possibilities that many companies have never before experienced. Rather than just extracting data, management at various levels can set up actionable Key Performance Indicator (KPI) alerts that act as a dashboard for the business. Analysis and queries using the same detailed data up and down the organization bring uniformity to the analytical and reporting process.
The benefits? For the first time, management has complete access to data across all systems in the enterprise. Objectives and KPIs can be set up to sharpen management decision making, and to keep senior management informed about the results on a real-time basis as shown in Figure 1: Solving Data Problems With BI Solutions.
Getting Your Personal Dashboard of KPIs and Analytics
Think for a minute, what data do you want to gain access to across your business? What information do you, as a member of senior management, need to run the business? Figure 2: Defining Your Personal Dashboard and Analytics shows how a company president in one of our client companies interpreted what she wanted, seeing what the benefits and data could be. When you look at this menu, you can see that much of what is included isn’t found in any one information system—and a number of these analyses and KPIs are created by including data mixed and matched between information systems.
Defining Your Personal Dashboard and Analytics
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Business intelligence systems with KPI dashboard alerts are a reality today.
Using Inventory Data Across the Enterprise
To go into more depth, Figure 3: Using Inventory Data Across the Enterprise shows how various managers can derive benefit from business intelligence systems tailored to inventory management. Inventory is the largest balance sheet asset in most businesses. Its effective management largely determines your level of customer service and profits. Suppose management had an ability not currently available to them: the ability to easily analyze some key inventory conditions. Here are a few examples:
- Inventory ageing. Age of inventory across the business and by product/SKU for various inventory statuses (active, inactive, future and return to vendor) by warehouse and by inventory control manager. One of our clients found that 30% of their inventory was older than 12 months. Having access to this view allows top management to continually stay on top of products that are not selling. The merchants can schedule to liquidate overstocks and slow-selling merchandise regularly.
- Inventory carrying costs. Costs of maintaining inventory in the company’s warehouse, including rent, utilities, insurance, taxes, fulfillment labor costs and the opportunity cost of having capital tied up. While inventory control applications have the on-hand quantity and dollars, financial management may want to develop a fully burdened cost for the inventory to more accurately reflect performance.
- Gross margin return on investment (GMROI). By category, product and inventory control manager. GMROI analyzes a firm's ability to turn inventory into cash above the cost of the inventory. It is calculated by dividing the gross margin by the average inventory cost. Senior management wants to judge the firm’s ability to turn inventory into cash.
- Customer service measured with fill rates. Initial item and initial customer order fill rate analysis, and final item and final customer order fill rates by category and product. Many companies measure back orders daily, but they don’t measure how well the customer is being serviced—in other words what percent of orders are shipped complete. We find the initial customer order fill rate to be 10 points lower than the line item fill rate in many businesses. For example, a fashion apparel business may have a difficult time achieving an initial order fill rate above 70% because of the newness of the style and the inability to reorder. However, a home décor business can achieve an order fill rate of 85% or higher.
- Back order cost analysis. To identify the total cost of being out of stock, both by product and by categories that are creating the biggest issues and expenses. Cost of back orders takes into account the total back order history by product for costs such as call center (“Where is my back order?”), second order picks and packing material, loss of shipping and processing revenue, etc. Most companies report back orders daily. There are few systems that keep track of the cumulative back order costs by product throughout the year. What our studies in hundreds of companies show is that back ordered merchandise costs $7 to $12 for each backordered unit of product.
Return On Investment (ROI)
There are great benefits to the organization when data can be shared across the enterprise and used for department analysis. We believe that these business intelligence applications will provide a positive ROI in 12 to 18 months, by enabling:
- In the inventory control areas, you will be able to optimize inventory levels for the first time, taking into account initial order fill rates (service levels), inventory and planned turnover objectives.
- In merchandising, you can expect to develop merchandise analysis by channel and across the enterprise to better understand how your multichannel business sells product. Vendor scorecards combine purchasing, demand and sales history, and receipt processing data.
- The ability to put together distribution center productivity and service level metrics in receiving, checking, picking, packing and shipping. These include cost per order and service levels in departments such as receiving and returns processing.
- Similar productivity data will be at your fingertips from the call center, with service levels for call abandonment rate, length of call, calls in queue, etc. as well as cost per transaction, cost per call and contacts per order.
- One of the biggest benefits to management is to get back in touch with the business from an analytical perspective. KPIs can easily be set up and changed to monitor performance in your areas of responsibility.
Using Inventory Data Across the Enterprise
Summary
What’s the cost of not having timely and accurate information to manage and control your business? There is an old industrial engineering axiom that says, “You can’t improve something you haven’t measured.” Worse, even if you have measured it, you still can’t improve something if you can’t get accurate readings, or if you have multiple measurements that don’t agree. With business intelligence systems, the ability to have instant access to all the most important data needed to make decisions is now a reality.