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I sat down for a discussion with the CEO of a local non for profit in Illinois. He spoke of his frustration with their current IT systems. The organization with a multi-million dollar annual budget provides affordable housing and adult education programs. As with many NFPs, the organization’s lifeblood is the generosity of donors and grants from companies and the government. These organizations must be efficient with both their people and financial resources.
During the conversation, the CEO wanted me to explain why he had separate systems for tracking donors, program operations, and grants. In his mind, these activities were all related. Donor engagement and grants were all based on the success of their programs. He saw the underlying data as a way of unlocking the full potential of his organization.
For example, if the operations management team could leverage program data, they could disperse resources in parts of the region that needed the most help. In turn, that data enabled the ability to send messages to donors in targeted campaigns based on a historical interest in programs. Additionally, the program data feeds better grant applications increasing the efficiency and reach of the programs.
With their current systems, there is no practical way to correlate the data and drive decisions based on that data. Without mentioning the term, the CEO described an Intelligent ERP system.
Making it Real
The CEO of the NFP is sitting at the point of frustration. How does the world of an Intelligent ERP solution look? I have an example from my career that I will anonymize to maintain customer privacy. We’ll reference the customer as Acme. What happens when you have a product at the top of its class in sales and effectiveness, but you can’t get the users to follow the instructions?
Acme had precisely this problem. However, it hadn’t always been the case. Early in the product lifecycle, the organization offered a white-glove service. Whenever a new customer purchased the product, a company specialist would call and walk the new customer through the use of the product. The CRM system data showed its increased use of the system and extraordinarily strong customer retention rates.
Acme’s white-glove customer service could not keep up with the product’s sales strength. As a result, both product usage and customer retention declined. Not a challenge in the short-term, the decline in customer retention would impact the expected growth of product sales.
Acme had a classic data problem. Just as our NFP CEO wanted to leverage data to direct limited resources, Acme wanted to leverage data to orchestrate its white-glove service.
The difference between the two organizations, Acme had invested in an intelligent ERP solution.
Leaders at Acme engaged data scientists to analyze data from the sales system with industry data to create a ranking system. The ranking system determined which customers were most likely to need white glove customer support vs. which customer would respond to simple marketing reminders. The data scientist tweaked the algorithms based on response rates within the different customer personas.
Acme experienced a marked improvement in system use and continues its market-leading position.
Where do you start?
First, you can look toward industry thoughts and observations from myself and my peers. Next, look to your existing ERP vendor. Begin by asking basic questions.
– How well does your ERP vendor or systems integrator know your industry?
– How have they helped other companies in your industry leverage data?
These are, of course, table stakes. Ask them the second level questions. What are the technical hurdles as you start to leverage data to drive decisions?
I’ll give you a hint. Older ERP solutions struggle with performance in answering these complex business queries. What seems like a simple question in the Acme example, “Who needs our help the most,” becomes a set of challenging technical issues.
– Where is the sales data?
– Where is the industry data?
– How do I get it in the same system to query securely?
– What system performance is needed to analyze the data?
– How do my data scientists and business users interface with the data?
– How do I refresh the system data?
The above questions are all but a small excerpt of the asks when searching for an ERP and SI that can help deliver an Intelligent ERP system. After implementation, the hard challenges start. Without exception, I’ve discovered post-implementation of new ERP capabilities – end users begin asking more prominent and challenging questions. The hunger for data and the ability to process that data becomes unyielding. From a practical perspective, end-users were never able to answer the basic questions around their data. Once you implement an ERP capable of processing your existing data, you find how far behind the speed of business your organization has fallen.
You must talk to other business leaders and technologists within your industry. Consider joining user groups for your target ERP solution and attend the virtual meetings. It is here where you’ll find a wealth of information around not the challenges of implementation but the ongoing demands of delivering on the promise of the Intelligent ERP. Are you still wondering about the ROI of the Intelligent ERP? Learn more about how to Lead the Modernization of your business.
Share your thoughts
We want to hear from you. Are you at the beginning of your intelligent ERP journey and have questions? Or, are you seasoned in delivering on concepts such as in-memory databases? Share your journey on your favorite social media platform with the hashtag #IntelligentERP.