Gain a Competitive Edge by Developing a Data Hierarchy
by Jackie Biallas
[basic-code]™ has helped companies gain a competitive edge by organizing their data and giving them visibility into the intelligence it provides. A well-thought out hierarchy and classification of attributes can help a business strategize and make decisions that increase operational performance.
[basic-code]™ helped one client develop a new hierarchy for their assortment of merchandise. Once the products were categorized and attributes were assigned, the company was able to see where there was duplication in their assortment. Unproductive categories and themes were identified. Less profitable SKUs were liquidated. The categories and themes that were the most profitable were capitalized on. Turnover increased from 1.5 to 3.2.
By using [basic-code]’s trend analysis, another client was able to guide their art department to focus on developing art for emerging trends. Data within the hierarchies and attributes provided insight into customer demand and volume potential. This insight helped improve productivity by reducing wasted time on less likely product, and maximized efforts on trend right product, answering the customer demand. Data can be sliced and diced to gain insights into early trends and whitespace in the marketplace.
A hierarchy is a method of organizing data in a table, acknowledging that one value encompasses all the values beneath it, in a tree-like structure. In a hierarchy, each “child” only has one “parent”, but a parent may have multiple children. For example, a manufacturer may have a hierarchy similar to this:
The information is then integrated into a database, consisting of all the records for the items that the manufacturer carries. The hierarchy table should be arranged so each row is a single sample (e.g. Part number) and each column is a single variable (e.g. Dept, Category, Attribute).
It is important that the attributes represent the key selling properties of the item. It is also important that the hierarchy be complete and accurate. If values are missing from the table or incorrect, the resulting analysis will be inaccurate because data from items that should have been included within a category is not included. Or, if the classification is incorrect, the data will be included in the wrong category.
BENEFITS OF A DATA HIERARCHY
Once the hierarchy has been established and the sales and inventory data are entered into the database, the information can be filtered, sorted, or manipulated to extract valuable insights into how departments, categories, or attributes are performing. Charts and graphs can be created to provide visualization into category performance.
Businesses can gain early reads on trends to give them a competitive edge. In addition, they can determine if there is any whitespace in the marketplace. For example, a product assortment may have three top-selling attributes, but is missing an item that possesses all three of these attributes together. [basic-code] ™ has helped companies define their hierarchy and product attributes, giving them the vision into their assortments. By determining the whitespace, new products have been developed and become top sellers.
By taking the time to establish a meaningful hierarchy, businesses can reap the rewards from the valuable insights it can provide. Contact [basic-code] ™ for a demo on how your company’s data can help you gain a competitive edge! www.basic-code.com
Companies that achieve the holy grail of Inventory Optimization (IO) realize maximum profit by holding the least amount of inventory necessary, while still fulfilling consumer demands and achieving fill rate goals. By matching supply to expected demand, companies reduce the cost of carrying inventory and increase cash flow and operational efficiencies.
An excess of inventory can cause many problems for a company. The typical cost of carrying inventory is at least ten percent of the inventory value. Excess inventory takes up space and cash flow that could be used for profitable inventory. It can be damaged, expire, or become obsolete, forcing the company to write off the inventory.
There are many challenges to achieving inventory optimization. Increased globalization lengthens transit times, increasing mergers and acquisitions often result in compromised data integrity, stringent customer service level agreements pressure companies to carry more inventory than necessary, and multi-channel and omni-channel distribution can complicate the collection of data. In addition, brick and mortar are increasingly competing against online retailers, trying to manage inventory at hundreds (or thousands) of locations while their competition may have just one location.
How to Achieve IO:
First, products and inventory should be classified into ABC categories according to their priority. Different products will have differing profitability and seasonality, just as customers or sales channels may be of differing priorities. Sales usually follow the 80/20 Rule, where the top 20% of the products produce 80% of the sales. By categorizing products in this way, a company may realize that they are over-assorted and may move to liquidate excess inventory immediately, thus saving themselves the inventory carrying costs associated with that inventory.
Next, companies must determine what level of service they can afford and what level their customers are willing to pay for. The relationship between customer service levels and inventory cost is non-linear, meaning the amount of inventory needed increases much faster than the level of customer satisfaction once you hit a certain point. Because products have been categorized by priority, it is clear that not all products have the same service level goals.
A company can then use demand forecasting to determine future inventory needs, factoring in sales curves, lead times, velocity, and criticality. This process must meet the KPI’s of the company, and must be continually monitored for changes, so improvements can be made. Because of the increasing complexity of the marketplace, it is important to have tools, such as a forecasting system, that can gather the data from the multiple sources and provide visibility to the inventory.
As a product’s sales slow, it is not hitting its inventory turn goals, and the product becomes obsolete. It is imperative that a company takes action to liquidate slow selling or unprofitable items in a timelymanner. The faster slow-selling products are removed from inventory, the faster they can be replaced by more profitable, better-selling items.
An added benefit of inventory optimization is the efficiencies gained in the warehouse. Because the products are categorized by priority, they can be assigned locations in the warehouse to reflect that. Operational efficiencies are gained when faster-moving product is housed closer to the outbound stations. By not holding excess inventory, costs are saved because the product takes up less space and fewer footsteps are needed to fulfill orders.
Despite the challenges to achieving Inventory Optimization, it can be done, especially with the right tools in place. Companies can gain an edge over their competition by improving their efficiency and cash flow.