More than three thousand years ago, the Chinese developed a strategy board game, called Go. It’s a complex, confounding game, but some have mastered it . . . or so they thought.
One day, a somewhat unconventional player came on the scene and began making moves no other player could comprehend. The player was artificially intelligent. It was using strategies it developed on its own – completely. It was only programmed with the basic rules of Go, not any human expertise or prior gameplays.
Depending on your perspective, this is either terrifying or exciting. The future of artificial intelligence (AI) is probably a mix of both. However, in the realm of ERP software, AI falls more into the “exciting” category. The AI within ERP systems is becoming increasingly advanced, and organizations are using this AI in conjunction with business intelligence to reveal new ways of improving operational efficiency and increasing customer satisfaction.
AI Functionality in Modern ERP Systems
While ERP software uses data to make basic predictions, AI uses this data to provide real-time recommendations based on multiple sources of data, both internal and external. AI augments the insights from your BI solution by providing what’s known as “prescriptive analytics,” which enables organizations to input hypothetical scenarios as AI calculates possible outcomes and suggests alternative solutions. AI uses machine learning to build its own logic for solving problems. All it needs is access to your data sources – your ERP system, cloud applications, IoT, mobile devices, etc.
Most organizations have so much data that it can be difficult to determine what data matters. If you think in terms of what matters to your different business functions, prioritizing data becomes easier. You can apply AI to any area of your business to gain competitive advantage.
How to Define a Business Intelligence Strategy
Before you select a BI solution or an ERP system with BI functionality, you should develop a business intelligence strategy so you can evaluate AI functionality in light of your business needs. Here are five steps that will prepare you for the ultimate AI and BI mashup:
1. Determine key stakeholders
Contrary to popular thought, the IT department isn’t the main stakeholder in a BI initiative. Business intelligence should be owned and accessed by all areas of your organization. Executives, of course, have a vested interest in business intelligence, but so do department managers. Today’s BI tools are intuitive so you may have more end-users than expected. Each of these stakeholders rely on business intelligence to inform decisions and achieve objectives. If these objectives align with corporate strategy, they should be part of your business intelligence strategy.
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2. Assess your current state
What is your current portfolio of enterprise systems and IT infrastructure? What are your current business processes? What’s your organization’s overall strategy? This knowledge will help you determine what’s working and what’s not. For example, maybe you’re storing data in multiple places but you need one version of truth. Pain points like this are an opportunity for improvement when defining your business intelligence strategy. You should also assess your current AI and BI functionality and determine if its advanced enough to “think outside the box” and provide your organizational competitive advantage.
3. Set KPIs
You probably have more data than you know what to do with. You can prioritize this data by determining what KPIs you need to track based on your business goals. Creating a data dictionary will help you align stakeholders when it comes to calculating and interpreting different KPIs. Most importantly, you should develop a strategy for acting on business intelligence. While AI is advanced, it can’t execute a full organizational change management plan and it can’t write marketing collateral for you – yet.
4. Evaluate your options
Your organization might need an entirely new ERP system with enhanced BI functionality and advanced AI. Alternatively, you might need a BI solution that fits with your current best-of-breed portfolio. Other variables to consider include scalability, level of customization and on-premise vs. cloud deployment. BI solutions in the cloud typically are self-service, allowing users to easily run queries and produce immediate reports. When evaluating AI functionality, you should consider ease-of-use. More advanced AI often requires more advanced statistical and programming knowledge.
5. Obtain buy-in
Business intelligence is only beneficial if employees use it. They won’t use it unless they know how and understand why. If you already have executive buy-in, you can develop a communications plan to help employees understand why you’re investing in a new BI solution. You should also develop a full organizational change management plan that addresses cultural barriers and emphasizes system training.
A Note About Artificial Intelligence
Some people will claim that true AI does not yet exist. While a perfect replica of the human mind doesn’t exist, we have designed AI systems that use human reasoning as a model. Definitions may differ, but the concept remains the same: machine intelligence imitates human reasoning to provide immediate insights humans might not conceive after years of contemplation.
Panorama’s ERP consultants can help your company develop a business intelligence strategy that leverages AI. Our team is experienced with hundreds of ERP systems, many of which have machine learning capabilities.