Artificial intelligence is top-of-mind as retailers look for ways to integrate AI into both the front and back ends of the business. AI can have significant benefits in retail; however, many retail organizations do not have the foundation in place for AI to be successful and deliver results.
AI in retail
AI is used in multiple areas across retail, from consumer product suggestions to merchandise demand forecasting and inventory allocation. In this article, we focus on the AI that involves data analytics, planning and forecasting, all for the goal of improving the customer experience.
The purpose of this AI is to enable better decision-making through gleaning faster and more accurate pictures from your data and other signals. To optimize AI, it is imperative that your organization be ready to use it, trust its output and act upon the insight it provides.
To ensure there is a foundation in place and make the AI worthwhile, you should focus on the people, processes and technology of your business.
Setting the Foundation
People
People are the foundation of any successful retail organization. AI is not meant to replace people in retail, but rather to provide a deeper understanding of the business. Associates will still need to work behind the scenes, acting upon the insights derived from AI. Ensuring that the organization is ready to work with AI is the first step in creating the foundation. The following steps will help you accomplish this.
1. Define your organization. Determine where your organization sits on the data utilization continuum. Are you sophisticated and using mature engines and data management strategies, or are you a beginner? Does the organization trust the data it has and utilize the data as it sits? Understanding this is the first step to guiding your path forward.
2. Determine your 'why'. Why are you considering AI? What are your goals? Ask these questions and then determine if AI will truly help you reach those goals and what else is missing that could contribute to reaching them.
3. Prepare your people. The people of your organization will utilize AI, so it is important to prepare them before implementing it. Talk with your associates and plan to help them understand the 'why' behind the AI.
Process
AI cannot fix a broken business practice. In most cases, AI will expose existing vulnerabilities in your process. Organizations that leverage AI and recognize its full benefit have processes with a clearly defined owner and outlined roles and responsibilities for each key input and output on an agreed upon timeline.
1. Implement process methodology. Create a detailed process for how you will ingest, utilize and produce data as well as who will be using that data. Without this foundation, data would exist for little reason and would not be informing business decisions.
2. Eliminate siloes. A siloed organization cannot leverage data in an ordered way. Foster a collaborative environment to ensure understanding of who does what with the data and how it is shared.
3. Implement change management. Though often overlooked, change management is a key strategy to increasing the chances of a successful outcome through increasing adoption by the user community. It is a fundamental element in the implementation of a new process, organizational structure and/or technology investment.
Technology
Master data management creates a single source of data truth across your enterprise. This is an important part of the foundation for AI because it ensures that the data is ready to be used throughout your organization.
1. Implement MDM strategies. Implement a data governance model that allows your organization to maintain data integrity and keeps data enterprise ready. This could be a process-first, technology enablement approach which aligns people, process and technology.
2. Maintain data traceability. It is important to know where your data started, how it has been manipulated and where it ends up. Organize your data to understand its components, including who owns it, how it is being calculated and manipulated, where it is catalogued and what systems it flows to and from.
3. Define the data. Understanding the meaning of each data element is imperative to acting upon the key learnings of AI.
AI is a great tool for increasing the value of data within an organization, but without a solid foundation, AI will not be as successful as needed. Building the infrastructure across people, process and technology is the first step to having a thriving, data-centric retail organization.