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10 Ways To Improve Cloud ERP With AI And Machine Learning

Capitalizing on new digital business models and the growth opportunities they provide are forcing companies to re-evaluate ERP’s role. Made inflexible by years of customization, legacy ERP systems aren’t delivering what digital business models need today to scale and grow.

Legacy ERP systems were purpose-built to excel at production consistency first at the expense of flexibility and responsiveness to customers’ changing requirements. By taking a business case-based approach to integrating Artificial Intelligence (AI) and machine learning into their platforms, Cloud ERP providers can fill the gap legacy ERP systems can’t.

Closing Legacy ERP Gaps With Greater Intelligence And Insight

Companies need to be able to respond quickly to unexpected, unfamiliar and unforeseen dilemmas with smart decisions fast for new digital business models to succeed. That’s not possible today with legacy ERP systems. Legacy IT technology stacks and the ERP systems they are built on aren’t designed to deliver the data needed most.

That’s all changing fast. A clear, compelling business model and successful execution of its related strategies are what all successful Cloud ERP implementations share. Cloud ERP platforms and apps provide organizations the flexibility they need to prioritize growth plans over IT constraints. And many have taken an Application Programming Interface (API) approach to integrate with legacy ERP systems to gain the incremental data these systems provide. In today’s era of Cloud ERP, rip-and-replace isn’t as commonplace as reorganizing entire IT architectures for greater speed, scale, and customer transparency using cloud-first platforms.

New business models thrive when an ERP system is constantly learning. That’s one of the greatest gaps between what Cloud ERP platforms’ potential and where their legacy counterparts are today. Cloud platforms provide greater integration options and more flexibility to customize applications and improve usability which is one of the biggest drawbacks of legacy ERP systems. Designed to deliver results by providing AI- and machine learning insights, Cloud ERP platforms, and apps can rejuvenate ERP systems and their contributions to business growth.

The following are the 10 ways to improve Cloud ERP with AI and machine learning, bridging the information gap with legacy ERP systems:

  1. Cloud ERP platforms need to create and strengthen a self-learning knowledge system that orchestrates AI and machine learning from the shop floor to the top floor and across supplier networks. Having a cloud-based infrastructure that integrates core ERP Web Services, apps, and real-time monitoring to deliver a steady stream of data to AI and machine learning algorithms accelerates how quickly the entire system learns. The Cloud ERP platform integration roadmap needs to include APIs and Web Services to connect with the many suppliers and buyer systems outside the walls of a manufacturer while integrating with legacy ERP systems to aggregate and analyze the decades of data they have generated.

  1. Virtual agents have the potential to redefine many areas of manufacturing operations, from pick-by-voice systems to advanced diagnostics. Apple’s Siri, Amazon’s Alexa, Google Voice, and Microsoft Cortana have the potential to be modified to streamline operations tasks and processes, bringing contextual guidance and direction to complex tasks. An example of one task virtual agents are being used for today is guiding production workers to select from the correct product bin as required by the Bill of Materials. Machinery manufacturers are piloting voice agents that can provide detailed work instructions that streamline configure-to-order and engineer-to-order production. Amazon has successfully partnered with automotive manufacturers and has the most design wins as of today. They could easily replicate this success with machinery manufacturers.

  1. Design in the Internet of Things (IoT) support at the data structure level to realize quick wins as data collection pilots go live and scale. Cloud ERP platforms have the potential to capitalize on the massive data stream IoT devices are generating today by designing in support at the data structure level first. Providing IoT-based data to AI and machine learning apps continually will bridge the intelligence gap many companies face today as they pursue new business models. Capgemini has provided an analysis of IoT use cases shown below, highlighting how production asset maintenance and asset tracking are quick wins waiting to happen. Cloud ERP platforms can accelerate them by designing in IoT support.

  1. AI and machine learning can provide insights into how Overall Equipment Effectiveness (OEE) can be improved that aren’t apparent today. Manufacturers will welcome the opportunity to have greater insights into how they can stabilize then normalize OEE performance across their shop floors. When a Cloud ERP platform serves as an always-learning knowledge system, real-time monitoring data from machinery and production assets provide much-needed insights into areas for improvement and what’s going well on the shop floor.

  1. Designing machine learning algorithms into track-and-traceability to predict which lots from which suppliers are most likely to be of the highest or lowest quality. Machine learning algorithms excel at finding patterns in diverse data sets by continually applying constraint-based algorithms. Suppliers vary widely in their quality and delivery schedule performance levels. Using machine learning, it’s possible to create a track-and-trace application that could indicate which lot from which supplier is the riskiest and those that are of exceptional quality as well.
  2. Cloud ERP providers need to pay attention to how they can help close the configuration gap that exists between PLM, CAD, ERP and CRM systems by using AI and machine learning. The most successful product configuration strategies rely on a single, lifecycle-based view of product configurations. They’re able to alleviate the conflicts between how engineering designs a product with CAD and PLM, how sales & marketing sell it with CRM, and how manufacturing builds it with an ERP system. AI and machine learning can enable configuration lifecycle management and avert lost time and sales, streamlining CPQ and product configuration strategies in the process.
  3. Improving demand forecasting accuracy and enabling better collaboration with suppliers based on insights from machine learning-based predictive models is attainable with higher quality data. By creating a self-learning knowledge system, Cloud ERP providers can vastly improve data latency rates that lead to higher forecast accuracy. Factoring in sales, marketing, and promotional programs further fine-tunes forecast accuracy.
  4. Reducing equipment breakdowns and increasing asset utilization by analyzing machine-level data to determine when a given part needs to be replaced. It’s possible to capture a steady stream of data on each machine’s health level using sensors equipped with an IP address. Cloud ERP providers have a great opportunity to capture machine-level data and use machine learning techniques to find patterns in production performance by using a production floor’s entire data set. This is especially important in process industries where machinery breakdowns lead to lost sales. Oil refineries are using machine learning models comprise more than 1,000 variables related to material input, output and process perimeters including weather conditions to estimate equipment failures.
  5. Implementing self-learning algorithms that use production incident reports to predict production problems on assembly lines needs to happen in Cloud ERP platforms. A local aircraft manufacturer is doing this today by using predictive modeling and machine learning to compare past incident reports. With legacy ERP systems these problems would have gone undetected and turned into production slowdowns or worse, the line having to stop.
  6. Improving product quality by having machine learning algorithms aggregate, analyze and continually learn from supplier inspection, quality control, Return Material Authorization (RMA) and product failure data. Cloud ERP platforms are in a unique position of being able to scale across the entire lifecycle of a product and capture quality data from the supplier to the customer. With legacy ERP systems manufacturers most often rely on an analysis of scrap materials by type or caused followed by RMAs. It’s time to get to the truth about why products fail, and machine learning can deliver the insights to get there.

6 Ways Cloud ERP Is Revolutionizing How Services Deliver Results

  • Cloud ERP is the fastest growing sector of the global ERP market with services-based businesses driving the majority of new revenue growth.
  • Legacy Services ERP providers excel at meeting professional & consulting services information needs yet often lack the flexibility and speed to support entirely new services business models.
  • Configure-Price-Quote (CPQ) is quickly emerging as a must-have feature in Services-based Cloud ERP suites.

From globally-based telecommunications providers to small & medium businesses (SMBs) launching new subscription-based services, the intensity to innovate has never been stronger. Legacy Services ERP and Cloud ERP vendors are responding differently to the urgent needs their prospects and customers have with new apps and suites that can help launch new business models and ventures.

Services-based Cloud ERP providers are reacting by accelerating improvements to Professional Services Automation (PSA), Financials, and questioning if their existing Human Capital Management (HCM) suite can scale now and in the future. Vertical industry specialization is a must-have in many services businesses as well.  Factoring all these customer expectations and requirements along with real-time responsiveness into a roadmap deliverable in 12 months or less is daunting.  Making good on the promises of ambitious roadmaps that includes biannual release cycles is how born-in-the-Cloud ERP providers will gain new customers including winning many away from legacy ERP providers who can’t react as fast.

The following key takeaways are based on ongoing discussions with global telecommunications providers, hosters and business & professional services providers actively evaluating Cloud ERP suites:

  • Roadmaps that reflect a biyearly release cadence complete with user experience upgrades are the new normal for Cloud ERP providers. Capitalizing on the strengths of the Salesforce platform makes this much easier to accomplish than attempting to create entirely new releases every six months based on unique code lines. FinancialForceKenandy and Sage have built their Cloud ERP suites on the Salesforce platform specifically for this reason. Of the three, only FinancialForce has provided detailed product roadmaps that specifically call out support for evolving services business models, multiple user interface (UI) refreshes and new features based on customer needs. FinancialForce is also one of the only Cloud ERP providers to publish their Application Programming Interfaces (APIs) already to support their current and next generation user interfaces.
  • Cloud ERP leaders are collaborators in the creation of new APIs with their cloud platform provider with a focus on analytics, integration and real-time application response. Overcoming the challenges of continually improving platform-based applications and suites need to start with strong collaboration around API development. FinancialForce’s decision to hire Tod Nielsen, former Executive Vice President, Platform at Salesforce as their CEO in January of this year reflects how important platform integration and an API-first integration strategy is to compete in the Cloud ERP marketplace today. Look for FinancialForce to have a break-out year in the areas of platform and partner integration.
  • Analytics designed into the platform so customers can create real-time dashboards and support the services opportunity-to-revenue lifecycle. Real-time data is the fuel that gets new service business models off the ground. When a new release of a Cloud ERP app is designed, it has to include real-time Application Programming Interface (API) links to its cloud platform so customers can scale their analytics and reporting to succeed. What’s most important about this from a product standpoint is designing in the scale to flex and support an entire opportunity-to-revenue lifecycle.
  • Having customer & partner councils involved in key phases of development including roadmap reviews, User Acceptance Testing (UAT) and API beta testing are becoming common.  There’s a noticeable difference in Cloud ERP apps and suites that have gone through UAT and API beta testing outside of engineering.  Customers find areas where speed and responsiveness can be improved and steps saved in getting workflows done. Beta testing APIs with partners and customers forces them to mature faster and scale further than if they had been tested in isolation, away from the market. FinancialForce in services and IQMS in manufacturing are two ERP providers who are excelling in this area today and their apps and suites show it.
  • New features added to the roadmap are prioritized by revenue potential for customers first with billing, subscriptions, and pricing being the most urgent. Building Cloud ERP apps and suites on a platform free up development time to solve challenging, complex customer problems. Billing, subscriptions, and pricing are the frameworks many services businesses are relying on to start new business models and fine-tune existing ones. Cloud ERP vendors who prioritize these have a clear view of what matters most to prospects and customers.
  • Live and build apps by the mantra “own the process, own the market”. Configure-Price-Quote (CPQ) and Quote-to-Cash (QTC) are two selling processes services and manufacturing companies rely on for revenue daily and struggle with. Born-in-the-cloud CPQ and QTC competitors on the Salesforce platform have the fastest moving roadmaps and release cadences of any across the platform’s broad ecosystem. The most innovative Services-focused Cloud ERP providers look to own opportunity-to-revenue with the same depth and expertise as the CPQ and QTC competitors do.

Why Cloud ERP Adoption Is Faster Than Gartner Predicts

200393880-001A recent study completed by Gartner titled Survey Analysis: Adoption of Cloud ERP, 2013 Through 2023 published on January 24, 2014, written by Nigel Rayner advises CIOs and application leaders of financial services institutions to “consider cloud ERP as a potential replacement for aging core ERP systems that are out of support or running on an old technology platforms (such as mainframes).“

The methodology is based on a survey of Gartner Research Circle members from North America, EMEA, APAC and Latin America from companies that range in size from $10M to $10B.

Key take-aways of the study including the following:

  • Including the 2% that already have core ERP in the cloud, a total of 47% of organizations surveyed plan to move their core ERP systems to the cloud within five years. This is because their ERP requirements tend to be focused around administrative ERP (financials, human capital management and procure-to-pay) where there is a wider range of cloud options (compared with manufacturing).
  • In aggregate, 30% of respondents say that the majority of their ERP systems will be on-premises for the foreseeable future as can be seen from the following graphic.

cloud adoption pie chart

  • 30% of organizations surveyed said they planned to keep the majority of their ERP systems on-premise for the foreseeable future.  Manufacturing organizations dominated this survey segment.

Why Cloud ERP Is Accelerating Faster Than Gartner Predicts

Two-tier ERP is the Trojan Horse of cloud ERP.  If Gartner had asked their respondents about if and how cloud-based ERP systems are being considered and used in two-tier ERP strategies globally, their survey and previous forecasts would have been significantly different.

From researching and working with manufacturers where two-tier ERP strategies make perfect sense for extending their legacy ERP systems to move into new markets, the following key take-aways emerge:

  • Achieving faster time-to-market while reducing cost of quality.  This is quickly turning into a year of transition for many supply chains, with the shift most noticeable in aerospace and defense.  Tighter project schedules driven by reduced budgets, coupled with more aggressive launch schedules is making this the year of the agile supplier.  Cloud-based ERP systems are essential to suppliers in this industry especially.
  • Legacy ERP systems lack scalability to support 21rst century compliance. One CIO who is a good friend jokingly refers to the legacy ERP systems populating each division of the manufacturing company he works for as fuel for his silos of excellence.  His point is that legacy ERP systems don’t have the data models to support the current quality management and compliance requirements corporate-wide and are relegated to siloed roles in his organization.  Cloud-based applications, specifically designed for ISO 9100, AS9100 Rev. C can do what legacy systems can’t, which is span across the aerospace manufacturer’s entire operations.
  • SaaS-based manufacturing and distribution software will increase from 22% in 2013 to 45% by 2023.  According to MintJutras, a leading research and advisory firm tracking ERP trends, a survey completed in 2013 shows SaaS-based applications will steadily grow from 22% of all manufacturing and distribution software installed to 45% within ten years.  The catalyst for much fo this growth will be two-tier ERP system adoption.
  • Microsoft’s New CEO knows the enterprise and cloud’s role in it. Satya Nadella has the daunting task of bringing innovation back into Microsoft.  As Anshu Sharma writes in his blog post today Satya Nadella: Microsoft, Coffee and the Relevance Question provides an excellent analysis of the challenges and paradoxes faced by the new Microsoft CEO.  It’s common knowledge in the Microsoft Partner community that the company runs one of the largest two-tier ERP system architectures in IT today, with an SAP R/3 instance in headquarters and Microsoft Dynamics AX running in each subsidiary.
  • All cloud ERP providers including Microsoft intend to monetize two-tier as much as they possibly can, architecting their respective Cloud OS strategies and enterprise suites to capitalize on it. Microsoft released an overview of their Cloud OS strategies in the following presentation, which provides a thorough overview of their perspective of the hosting market and how it relates to their apps business. Also included is the following graphic, Cloud OS: Innovation at Scale.  All of the factors taken together will drive up adoption of Microsoft Dynamics AX 2012 and streamline two-tier enterprise sales across all cloud ERP providers.  Last year at Microsoft Worldwide Partner Conference the announcement was made that Microsoft Dynamics AX 2012 would be available on Windows Azure in July, 2014.

cloud scale

  • Mobility is unifying the manufacturing shop floor to the top floor faster than anyone thinks.  In traditional ERP systems mobile platforms are most often used for material handling, warehouse management, traceability, quality management, logistics and service tracking. From the discussions I’ve had with CIOs and a few CEOs of manufacturing companies, there’s a high level of interest in analytics, alerts and approvals on Android and Apple tablets.  These apps and the speed of results they deliver are the new corporate bling. Intuitive, integrated and fast, these mobile apps make it possible for senior managers to check up on operations for wherever they are globally, in addition to approving contracts and being notified of events via alerts.  For Gartner’s assessment of cloud ERP to have been complete in this survey, mobility also needed to be covered
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