Crossing the chasm for S/4HANA adoption

The chasm is only as wide as you want it to be

The author, Geoffrey Moore, coined the term “crossing the chasm” in his book on disruptive technology marketing as a reference to solution providers trying to drive buyer adoption beyond early markets. The journey is characterized by crossing a metaphorical “chasm” representing the disconnect between the early adopters and buyers in the mainstream market.

Moore’s chasm also applies to SAP’s S/4HANA, an innovative technology that still has not achieved mainstream acceptance despite the hype. Our conversations with Gartner analysts and customers confirm S/4HANA adoption at barely 15% – the precipice of the chasm. This comes despite the product being in market for four years and backed by SAP’s marketing machine. Perhaps more importantly, only 50% of customers are capable of running S/4HANA today because they’re on older R3 4.x versions. Most of these companies are in the industrial manufacturing sector.

Source: Geoffrey Moore, “Crossing the Chasm”

So why is S/4HANA adoption taking so long? The benefits delivered through the SAP S/HANA are significant. Business owners get insights from real time data. Technology teams get a cost effective, high performance, cloud ready platform that supports innovation. But despite the game changing potential for S/4HANA, there’s still a lot of status quo inertia to overcome:

For many organizations, the company’s own SAP deployment becomes a world view of SAP. Experienced technical staffs have invested thousands of hours customizing and maintaining their SAP infrastructure just to keep the lights on. S/4HANA may not be well understood.
The current SAP infrastructure still works, even if it’s an older version no longer supported by SAP. This is easy to understand. My own mother uses an early NOKIA feature phone that’s more than 10 years old. She can still text, slowly. She can surf the web too… but very slowly. The point is her phone works, it meets her needs, she’s happy with it and she has no reason to change.
Most organizations have a limited appetite for time consuming and costly digital transformation initiatives, despite the promise of long term benefits. Resources, budget and time are scarce and the business case for justifying a major change may be undercut in pursuit of other projects with more immediate payback.
Not having a partner to provide necessary skills, along with industry insights and technology chops can be a significant barrier. Collaboration with the right partner provides value in developing a roadmap that considers cloud, security, the state of data and future demands of the business.

Now is the time to overtake inertia and rethink migration to S/4HANA. CIOs are under increased pressure to run lean in uncertain economic times, but digital transformation is accelerating. According to PWC, 78% of industrial manufacturers have begun their digital transformation journey. Remaining manufacturers who are just getting started need to make a real commitment or risk falling further behind.

Organizations need to determine the best migration path to S/4HANA. The best alternative will put their company on a path towards digital transformation at a sustainable rate and pace, delivering the right balance of immediate benefits and transformational change. For many manufacturers still running R3 4.x, taking the first step with a technical upgrade to SAP Business Suite ECC 6.0 on HANA (SoH) is an attractive option. A technical upgrade provides immediate benefits prior to the second step of migrating to S/4HANA with full capabilities.

Once the organization has transitioned to a supported version of SAP, there may also be an opportunity to get out from under the more expensive 3^rd party support contracts. However, those companies that have pocketed the AMS support expense by taking a DIY approach will have to make the call on support for SOH.

Companies get some valuable breathing room to plan for the final migration to S/4HANA once the technical upgrade to SoH is complete. Gaining time to plan this future roll-out while still getting the benefits of the technical upgrade may be the best reason of all for the two-step migration to S/4HANA.

The overall takeaway is that the “chasm” companies face in adopting S/4HANA is only as wide as companies want to make it. The two-step migration approach with a technical upgrade to Suite on HANA with future migration to S/4HANA provides immediate and valuable benefits to the business while deferring much of the pain associated with big transformational projects.

The numbers are in. The use of IoT and Machine Learning (ML)/Artificial Intelligence is exploding in the manufacturing market. Let’s look at the data:

The IoT segment is predicted to grow at a 29% Compound Annual Growth Rate (CAGR) to become a $45.3 billion market by 2022.
The machine learning market is expected to grow at an aggressive 44% CAGR, expanding from $1.4 billion in 2016 to $8.8 billion by 2022.
A recent survey shows 61%of organizations see machine learning/artificial Intelligence as the most significant data initiative for their company in 2018, and 58% of those respondents have run models in production.

With the IoT market already at critical mass and the ML/AI market rapidly moving towards the mainstream, CEOs can either take action now to stay ahead of the curve or risk falling behind.

Why is AI & ML technology adoption so pivotal?
Many manufacturers are struggling with volatile demand as well as complex, differentiated products. These market factors make inventory planning and supply chain optimization a constant struggle. It leads to inefficient operations that result in a volatile bottom line. IoT and ML technologies are disruptive to current manufacturing techniques, and companies that incorporate these technologies are dramatically changing their traditional cost and efficiency metrics.

AI & ML are revolutionizing manufacturing expectations
Incorporating IoT and ML increases productivity and efficiency, and the potential will only expand in the future. By providing integrated machine-to-machine communications, as well as gathering massive quantities of data for analytics, manufacturers are improving metrics throughout the supply chain and on the shop floor. The benefits of these technologies are myriad, assisting manufacturers by:

Increasing supply chain efficiency: The globalization of manufacturing has resulted in complex supply chains that include numerous providers, in increasingly diverse locations, so it is harder to react quickly to fluctuations in demand. Incorporating IoT devices in the supply chain provides precise information on current supply, demand, and the ability to track goods in transit. It provides real-time data analysis that enables organizations to react quickly to changes in demand and scale manufacturing in shorter timelines. In fact, McKinsey researched the German manufacturing market and posits that ML will reduce direct expenses by cutting transport and warehousing costs by 5 – 10% and reducing supply chain administration costs by 25 – 40%. In addition, it forecasts that ML predictive analytics will improve efficiency planning and lower supply chain forecasting errors by up to 50%, which will enable inventory reductions of 20 – 50%.
Improving inventory management and asset tracking: Machine learning algorithms and modeling are making it possible to optimize inventory across all distribution locations. It even enables companies to factor in variables, such as the weather and the economic climate that can impact demand and production.
Preventing downtime and reducing annual maintenance cost: IoT device sensors can identify and alert organizations of imminent machine failures, so floor managers can act quickly to order repairs during off-hours and avoid downtime. These devices can also track historical maintenance and performance information, sharing the data with ML-based predictive analytics tools to optimize your maintenance schedule. McKinsey posits that this process can reduce inspection costs by up to 25%, and lower overall maintenance costs by up to 10%.
Increase manufacturing productivity: Using IoT devices or programmable logic controllers, manufacturers can collate data from all machines to find efficiencies in the processes and equipment. In addition, organizations can increase yield by using IoT devices and sensors for early quality detection. By sensing quality issues sooner, organizations can drive down the costs of production and raw materials. McKinsey estimates that incorporating both IoT sensors and ML productivity tools can boost asset productivity by up to 20%.
Acquiring real-time data analytics: IoT devices can make the manufacturing floor more efficient by using real-time analytics from these interconnected devices. Instead of improving processes when a lag is noticed at the end of a shift, alerts can be triggered earlier in a shift, so the root cause can be identified and solved immediately.
Harnessing the power of predictive analytics: IoT devices can feed relevant information into machine learning technology to create an optimized, predictive and automated process.

As organizations compete in a globalized marketplace with increasingly tight margins, proper integration of IoT and ML into the manufacturing process can better predict customer demand and optimize inventory levels to ensure productivity without draining working capital.

How to re-define your business processes to incorporate IoT and ML
It is clear that AI and ML are critical for making manufacturing companies more productive and agile. The path to realizing the benefits of these technologies requires that you:

Transform your business processes to incorporate these new digital technologies.
Upgrade your enterprise resource planning software to incorporate AI and ML into your business processes.

The most effective way to redefine your business process is to work with a digital transformation consulting group. At ThoughtFocus, our team is composed of former CTOs, CIOs and VPs of operations, who know all of the best practices for creating innovative digital business processes that drive results across the entire value chain. We have established project methodologies that provide a clear vision for every step of your project, defining detailed business strategies, drafting innovative process designs and designing efficient implementations.

In addition to redefining your business processes, you need to update your business tools to integrate AI and ML. In good news, most manufacturing companies use SAP, and the new SAP S/4HANA platform has been completely re-designed to enable dramatically faster, more flexible, digital transformations. It provides the best platform to successfully incorporate IoT and ML into your manufacturing organization and maximize the value of your business. As an SAP Silver Partner, we have the expertise, proven methodologies and best practices to design and deploy innovative solutions that deliver value.

Ready to learn more? To see how ThoughtFocus can enhance the efficiency of your manufacturing process and supply chain, contact John Campanella, GM SAP Practice at jcampanella@thoughtfocus.com or +1-310-427-7654.