Everywhere you turn, technology is changing the way we work.
McKinsey & Company reports that companies spent in excess of $25 billion on artificial intelligence research and acquisition in 2016. The report also estimates that external investment in AI has tripled since 2013, and who knows how much it grew last year as it became a trending topic.
Of course, AI is just one of the new technologies we’re seeing that have the potential to transform the manufacturing industry with better forecasting, optimized production, targeted sales, and enhanced maintenance strategies.
But in order to take advantage of those opportunities, you need a strong digital foundation, including software. Digitally mature companies (those with a fully developed digital strategy that includes up-to-date software and the ability to innovate with new technologies quickly) are more likely to adopt AI, machine learning, and other transformative technologies for core activities.
Why is that important? Because digitally mature companies are 26% more profitable than less digitally savvy competitors within an industry vertical.
But upgrading your software can be expensive and time-consuming. That means doing so is not always a straightforward decision. So what are some other reasons you should consider doing it? Here are three of the most compelling.
Communication is essential for any business, but that’s especially true for manufacturing companies where getting the right message to the right person at the right time has a direct impact on profit margin. Software can improve communication efficiency by connecting employees in various departments in one system and making it easy to transfer information quickly without relying on printouts, spreadsheets, outdated email systems, or your assistant (however competent he or she may be).
Collaboration is essential in today’s workplace, and studies show that the right social technology can make employees more productive on the job. You can build communication tools into your ERP so employees can easily pick each other’s brains, communicate with colleagues in remote locations, and transmit the latest vital information to team members all within the system.
You can also incorporate tools to facilitate communication with external vendors and customers. Better communication means deeper understanding of customer needs and expectations as well as less down time during processing and shipping.
Profit generation depends on efficient processes that keep costs down and eliminate waste. Software streamlines those processes from end to end using automation and data management. Here are a few of the areas you can expect to see improvements:
Many of the tasks you perform on a daily basis can be automated within your software. These include production orders, shipping communications, cost calculations, billing, customer and supplier support, and quality control. And of course, automation means faster cycle times, fewer wasted hours, and lower costs.
Forbes predicts that factories of the future will all depend on AI to remain competitive. AI can perform routine jobs faster, incorporate flexible automation to adapt to new processes, perform quality control inspections, manage demand and production, and much more. The AI of the future will do much more than manage heavy lifting and repetitive production tasks. It will still do all those things, but it will also become an essential component of planning and production from start to finish.
IoT for Predictive Maintenance
IoT applications use data analysis to predict maintenance needs before a piece of equipment goes down. Some of these applications aim to reduce maintenance costs by up to 25% by capturing data in real time—before you lose production time.
Applications for machine learning in the manufacturing industry range from increased production capacity to product quality to supply chain optimization. Machine learning is designed to identify maximized outcomes based on data, surfacing in minutes the same insights and analysis that would take human workers weeks or months to comb through.
Too much or too little inventory can be costly. The right software can analyze supply and demand data over time so you can have the right inventory in stock at the right time.
Keep records and manage data within the system, from HR documents to shipping records to inventory. When all that information is stored in the software, it will be easier to find and retrieve the documents you want at any given time.
Artificial intelligence, machine learning, and data analysis are essential for decision-making in the manufacturing industry, too. Storing, sorting, analyzing, and reporting data efficiently is the first step toward making growth decisions that will give you a competitive edge.
If you currently have data stored in several different locations—or even on spreadsheets or paper—there are several things I can predict about your processes:
* Your reporting process isn’t as efficient as it could be.
* You have redundancies in your data.
* Your data is not real-time (at least not for everyone).
* Data entry takes longer than it should.
* You don’t have the right foundation to take advantage of new technology advances like AI, machine learning, and IoT.
I know these things are true because a faulty foundation will always deliver less-than-optimal results. At the HR Tech Conference in Las Vegas this fall, LeapGen CEO Jason Averbook compared this approach to data to putting frosting on a moldy cake.
The solution is to put the right software foundation in place first and then expand into some of the more exciting technology opportunities.
Once you take that step, you’ll have the tools you need to transform your decision-making process:
Simply by asking different questions and tracking the right data, you can tap into previously unrecognized opportunities for profit generation and cost savings. Business intelligence helps you identify process bottlenecks, improve efficiency, and reduce waste by giving you insights about warehouse procedures, supply chain opportunities, inventory management, equipment function, maintenance procedures, and much more. And when you make the leap into AI and IoT, those insights will happen more quickly and more precisely than ever.
Track and analyze customer demand, factory load, resource needs and availability, sequencing, scheduling, and delivery needs based on past trends and current production capacity.
Asset and Inventory Tracking
Track and manage tools, equipment, computer assets, delivery and receipts, parts, material consumptions, and inventory more efficiently. AI applications can also manage stocking and re-orders as needed, so that you don’t experience production delays.
Track purchase patterns so you can forecast customer demand over time and avoid stocking too much or too little inventory.
As efficient operations come to rely increasingly on clean, readily accessed data, a practical data management solution has become non-negotiable. Data management software should include robust solutions for data warehousing, access and sharing, security, archiving, backups, documentation, and analytics tools.
Effective reporting flows out of a solid data management strategy. Standard reports help you make better decisions as you monitor inventory, supply and demand patterns, overall equipment effectiveness (OEE), quality control, warehouse management, production history, material usage and the many other analytics that keep your company running on time and on budget.
We’re stepping into a new year, and we expect to see some significant technology developments in the coming months. Some pundits predict that the nature of manufacturing jobs will fundamentally shift from managing parts and processes to managing technology. They also predict that these changes will make manufacturers more efficient, more productive, and more profitable.
Putting the right software foundation in place now will position you to be ready for those developments and remain competitive in a rapidly changing industry. Don’t be left behind.