A key solution to this problem is to implement a centralized data warehouse for a single version of the truth. But changing the mindset from spreadsheets and reports to an analytical capability can be challenging as users must give up control of the data in exchange for more power to analyze the information. A lot of IT departments traditionally charged with rolling out supply chain analytics tools run into the same challenges, such as:
- How do we train users on this new application?
- How do we make it meaningful to ensure users will adopt the process and not go back to old methods of static reports or spreadsheets?
- What information do the users really need to meet their business goals?
Starting at the Top
A key first step is to have buy-in at the highest level of the organization. This provides many benefits because the entire organization from the top down is looking at the same KPIs and speaking the same language, and there is a clear form of communication when it comes to the metrics and KPIs that drive the business. This will ensure that everyone is working towards, and aware of, the business goals.
A great example of this comes from a Logility customer. The CEO records some of the user training videos himself and shares them with his whole organization. In his opinion, if the CEO is a user and an enthusiastic fan, there is no reason that all users should not be as well.
However, executives often have a different need from their supply chain analytics tool than other users working in specific departments. Executives look at high-level company metrics, while other departments such as Finance, Sales, and Operations work at a more analytical level. Trying to have one set of dashboards that answer the questions of these different groups of people will lead to frustration and lack of adoption by either group. Creating different dashboards for each department or cross-departmental dashboards for executives is a key first step to rolling out any analytical tool.
Creating cross-departmental dashboards is a simple process. One way to successfully accomplish this within Logility is to create an ‘executive’ or ‘summary’ data model that includes data from key areas of the business such as Sales, Finance, Operations, Inventory, and Production.
The KPIs that will be included on the dashboard should depend on the overall business needs and goals. As an example, KPIs such as Safety, Quality, Inventory, Cost and Delivery are often key in the supply chain space and should be included on the dashboard if those are of importance to the organization. The KPIs that drive the business will vary between organization, industry and verticals, however understanding these will help in the overall design of the dashboard and implementation of the data model.
- Identifying clear problems to solve will help the organization increase user adoption. Decreasing the rate of returns, increasing the accuracy of the inventory forecast, or decreasing costs while increasing profits are clear goals for everyone. Communicating these to users will increase the overall understanding of the need for a supply chain analytical tool as well as what they can gain from it.
- Make the tool accessible. Embedding Logility dashboards into applications that everyone accesses on a daily basis, such as SharePoint or an Intranet site, will help keep analytics front of mind. Ensuring that mobile device use is available and encouraged will help users access the tool anywhere and at any time.
- Combine data from multiple areas of the business and multiple datasets to ensure data governance is applied to the metrics being analyzed daily, so users are all speaking the same language when it comes to data.
- If users are hesitant to move to an analytical tool at first, use Logility Scheduled Reporting to push out reports directly to their inbox. Reports can be distributed in formats such as Excel and PDF, so they receive the familiarity of their previous report, along with the data governance in place.
- Keep the initial rollout simple. Start at the top with executive-level dashboards and reports and then move to departmental ones.
- Ensure that all users receive basic training at the beginning and partner with Logility to assist with initial training and development, as well as ongoing education.
- Ensure users understand the information being presented and not just the mouse and button clicks of the tool. If the data is being presented in an unfamiliar format, or if metrics are using a newer, standardized format, ensure this information is communicated.
Daniel Bachar is a Product Marketing Director for Advanced Analytics for Logility. Daniel brings more than 10 years of experience in sales, marketing, supply chain planning, and advanced analytics. He provides a unique blend of business and industry knowledge, leading successful efforts to integrate new technologies into effective supply chain solutions. His experience includes development, design and go-to-market strategy of supply chain and advanced analytics products, helping clients with complex business problems to achieve complete visibility into their supply chain operations.