While there are many capabilities involved in running a successful day-to-day business, there are some highly critical capabilities that are a basic part of securing a solid foundation as you are future-proofing. These critical capabilities should be reviewed, created, redesigned, and/or standardized
Inventory is one of a retailer’s largest assets and keeping inventory accurate is indeed a priority. Most retail executives subscribe to this mentality; however, time and time again retailer managers question their inventories across the supply chain for various reasons. An inordinate amount of time and energy continues to be expended trying to get a handle on inventory levels, communicating accurate stock levels to stores and customers through a variety of systems, and struggling to manage the buying process in a timely fashion.
While these challenges can be disguised as ‘data’ issues, many times we have found that poorly managed and undefined business processes are the culprits of inventory inaccuracy.
Parker Avery has published several point of views focused on inventory accuracy, including “Inventory Accuracy: Fundamental Strategies for Getting it Right,” and Omnichannel Inventory Accuracy Implications and Customer Impact.” Let’s look at some highlights and recommendations from these publications:
Review in-store receiving and store balancing processes and establish realistic, well-documented, and timely business processes to manage shipments/receipts and transfers
Ensure store associates understand the importance of scanning each and every item at the register to correctly decrement each item sold
Hold associates accountable for the results of these processes, where possible
Consider frequent physical inventories and timely system updates – (e.g. ABC categorization, fast movers/top volume items should be counted more frequently than other items to ensure on hands are consistently updated)
Implement an advanced way to track inventory in all repositories in real-time (e.g. integrated warehouse management system or WMS)
Strive to provide ‘near real-time’ inventory updates for all channels so customers and store associates are seeing accurate information
Provide real-time views of inventory on hand, on order, and in-transit by individual channel and consolidated to support better internal decision-making
Carefully determine which channel or store should receive credit for online sales—particularly for buy-online-pick-up-in-store or ship-from-store models—to enable predictability for future sales and support replenishment needs
Further, we take a deep dive into managing inventory on a global, omnichannel scale in our point of view, “Getting to Global: Managing Inventory in a Unified Commerce World.”
In today’s uber-connected, digital world, where information is absolutely critical to maintain any kind of viability, you must not only integrate your data, as we discussed earlier, but also have a solid handle on the state of your data, which is where data governance plays a key role.
Data governance is defined as the people, processes, and technology required to create standard and consistent handling of a retailer’s data across the business enterprise. It provides all data management practices with the foundation, strategy, and structure needed to ensure data is managed as a business asset and transformed into meaningful information. The key focus areas of data governance include availability, usability, consistency, data integrity, and information security. Time spent governing data when the product or customer master is set up will reduce delays in getting products to market or through the supply chain—as well as mitigate issues with customer data security and privacy—and greatly enhances data consistency.
A key component of an effective data governance program is that of the data steward. The data steward is a business role that ensures data governance processes are followed, guidelines enforced, and recommendations for improvement are reviewed and implemented.
The degree of data integrity and data quality will be the path to either success or demise for any organization.
Data integrity includes data validity, meaning it is accurate and consistently stored in the proper format, whereas data quality pertains to the completeness, timeliness and consistent state of information managed in an organization’s data warehouse. The following are some high-level steps to take relative to improving your data integrity:
Consider the best access points to capture data, so it is most accurate
Ensure the data sources are a result of sharp, well defined timely and stringent business processes throughout the organization
Consider precise and intelligent integration that can lead to accurate and timely data
Require your foundational systems to be easily upgraded to keep the organization up to date and increase adaptability to new solutions
The decision to invest and implement a separate data governance role depends on the size of the organization, but the topic should always be at the forefront of any initiative. Consistency in data management and data definition makes decisions and project design less complicated and change management less complex.