Artificial intelligence (AI) will have a direct impact on your business sometime soon. As larger companies begin integrating AI-driven software into their workflows, it will pressure adoption laggards to upgrade their legacy platforms.
Forward-thinking organizations are already preparing for a phenomenon known as hyperautomation, a subset of digital transformation that uses intelligent automation to improve business processes. Gartner’s definition of this:
Hyperautomation involves the orchestrated use of multiple technologies, tools, or platforms, including: artificial intelligence (AI), machine learning, event-driven software architecture, robotic process automation (RPA), business process management (BPM), and intelligent business process management suites (iBPMS), integration platform as a service (iPaaS), low-code/no-code tools, packaged software, and other types of decision, process, and task automation tools.
Significantly, this definition suggests that hyperautomation isn’t siloed but a set of integrated processes, systems, and technologies for automating operations, interacting with customers, viewing and managing the supply chain, and more. Hyperautomation links an integrated ecosystem of AI and automation tools that affect all these areas.
The overwhelming potential for AI in B2B businesses is also a drawback that contributes to analysis paralysis. Companies are stalling out at the starting line, doing little to nothing with AI because they don’t know how or where to apply it in their business. These companies often lack a key technology stakeholder with the vision and horsepower to redesign business workflows to leverage AI and automation.
Next steps in the transition to hyperautomation
Hyperautomation requires changes in technology, people, and processes. Analysis and strategic planning are always the first step toward any technology upgrade that affects human workflows.
Develop an intelligent automation leadership team to strategically analyze, implement, and oversee hyperautomation initiatives. The team should unite individuals with diverse skills, experiences, and perspectives to ensure comprehensive decision-making and successful implementation.
• Identify key organizational stakeholders directly or indirectly affected by automation. Ensure representation from various departments such as operations, IT, finance, legal/risk, human resources, and customer service. Select committee members with a mix of technical and business expertise.
• Obtain buy-in from top leadership. Executive support is crucial for the success of any new technology or business process initiative. Appoint a senior executive as the sponsor or chairperson of the intelligent automation leadership committee to demonstrate commitment from the highest levels.
• Define clear roles and responsibilities for each committee member. This will ensure accountability and a focused approach. Make sure the goals of the intelligent automation committee align with broader business objectives. Assign tasks such as identifying automation opportunities, evaluating technology solutions, overseeing implementation, and monitoring performance.
• Provide training and development opportunities. Committee members need to understand automation technologies and their potential impact on the business.
• Establish a risk management framework. The goal is to identify potential pitfalls associated with automation. Develop strategies for mitigating risks and handling unexpected challenges.
The next step involves a comprehensive assessment of processes. Identify key workflows, bottlenecks, and areas that can benefit from automation. Consider operational efficiency, customer experience, compliance requirements, and business strategy.
Finally, foster open communication within the team and the broader organization. Transparency is crucial for building trust and collaboration. Regularly update all stakeholders on the progress of automation initiatives, milestones achieved, and challenges faced.
Use cases for AI and automation — how and where we’re using it
There are myriad possible applications for intelligent automation across manufacturing, healthcare, government, distribution, and retail. McKinsey suggests that 50% of order management tasks have the potential to automate.
Today, distribution companies can apply intelligent automation to sales enablement and order management. It’s an area where AI can yield rapid-fire easy-to-measure ROI within lead generation, closed sales, and revenue production.
For example, California-based Pacific Coast Supply worked with DataXstream to automate order and payment processing workflows across 49 stores. Pacific Coast Supply Digital Transformation Manager Joe Valine says, “We took an effort that would take someone about 30 minutes to an hour a day and simplified it down to about 15 minutes. That impacted at least 50 employees every day for an hour. Call it $20 an hour … that adds up quickly on a 255-business-day work year.”
Crafco, the No. 1 packaged pavement preservation product company, uses DataXstream AI and automation in counter sales. They improved margins on total sales by 1.6% across their $450 million business.
Ultra Finishing Limited (now Roxor Group), the U.K.-based bathroom product manufacturer and distributor, implemented DataXstream to increase sales and customer satisfaction. Intelligent automation yielded a 15% increase in sales in 2019 and a 25% improvement in customer satisfaction. Order entry and processing speed and accuracy increased by 40%, and the costs of maintaining legacy systems dropped by 50%.
These examples illustrate the time savings and revenue generated with intelligent automation tools like DataXstream’s OMS+. Distribution is an industry that cries out for these tools; large order volumes, product line complexities, and supply chain challenges all can be tackled with hyperautomation. While many struggle with disjointed systems that slow them down, today we have the tools to turn things around.
The ROI of AI — how and what to measure
Tracking your return on investment (ROI) is critical. This year, Gartner expects organizations to lower operational costs by 30% by combining hyperautomation tools with redesigned operational workflows. But how will companies know when they’ve reached these milestones without tracking?
To measure the ROI of AI and automation start by assessing the costs and the benefits of implementing these technologies.
• Clearly define the objectives of implementing AI and automation. These objectives should align with the overall business goals, such as improving efficiency, reducing costs, enhancing customer satisfaction, or increasing accuracy.
• Identify and track specific KPIs that are relevant to your objectives. KPIs may include:
- Order fulfillment time
- Inventory turnover
- Order processing accuracy
- Labor costs
- Customer satisfaction
- Upselling/order add-ons
- New business
• Determine costs associated with implementing and maintaining AI and automation systems. Consider initial setup costs, ongoing maintenance, training, and other associated expenses.
• Evaluate the impact of AI and automation on the identified KPIs. Benefits may include:
- Reduced labor costs
- Increased productivity
- Improved accuracy and reduced errors
- Faster order processing
- Enhanced customer satisfaction
• Compare metrics before and after the implementation. This can quantify improvements, correlating them to technology.
• Convert KPIs into monetary values wherever possible. For example, if AI and automation lead to a reduction in order-processing time, calculate the associated cost savings.
• Consider the impact on customer satisfaction and loyalty. While these factors may be challenging to quantify in monetary terms, they are crucial for the long-term success of any distribution company.
• Determine the time frame for assessing ROI. You may realize some benefits immediately, while others might take time. Consider both short-term and long-term impacts.
• Assess potential risks and challenges associated with AI and automation implementation. Consider the risks of technology failure, employee resistance, or unforeseen issues that may impact the expected benefits.
• Establish a system for continuous monitoring and evaluation. Distributors should regularly review performance metrics and adjust strategies accordingly.
• Compare your company’s performance with industry benchmarks. This provides insights into your relative competitiveness and helps you identify areas for improvement.
• Finally, calculate ROI using the following formula:
DataXstream
The ROI calculation should be ongoing, and adjustments may be necessary as the business environment and technology landscape evolves. Regularly revisit and update your ROI analysis to ensure that your investment continues to provide value.
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