Unleashing the Power of Cloud to Accelerate Growth and Build Resilience
The concept of a “supply chain” was born out of the creation of the assembly line, dating back to the early 20th century. Each function, from planning to delivery, had its place. And if everyone did their part, just like a well-oiled machine, you could expect high margins and growth. It worked so well that as we modernized our supply chain management, introducing technology and automation to help us move faster and smarter, the foundation was still tied to the original linear, siloed, rigid approach.
What wasn’t accounted for is that our world today looks pretty different than it did in 1905. Or even than it did in 2015. Optimizing at the functional level to drive the very lowest cost will no longer produce the best possible results for the organization’s bottom line. These walled off systems can no longer handle the pace of change and cannot deliver the agility necessary to keep up with customer demand, market disruptions, and growing complexity.
Businesses leaders across industries know they need something different. They want a supply chain that’s modern, resilient, and fully optimized to deliver the greatest possible profit to their organizations. Who wouldn’t?
The challenge: Where do you start? In this blog, we’ll walk you through the key steps you should take to increase supply chain resilience and profitability by shifting to the cloud and taking full advantage of the technology innovation available today.
Step 1: Transitioning to the Cloud – Your Launchpad for Digital Transformation
Enterprises today want a supply chain that’s modern, resilient and fully optimized. And to get there they have to first make a leap over to the cloud. By shifting from on-premises to the cloud, you open your business up to a significantly higher level of agility and speed, so you can pivot and shift on the fly in response to supply chain disruptions.
You also gain the ability to consume innovation faster and cheaper. With on premise technology stacks, it’s time-consuming and expensive to upgrade to new functionality. But on the cloud, this can be done in minutes or days, versus months or years. And finally, you’re able to process information – running scenarios across merchandising, manufacturing, logistics, warehousing, and distribution – all at the same time with unconstrained computing power. You can scale up and scale down quickly, on-demand. Rather than using one CPU for 100 hours, you can use 100 CPUs for one hour, compressing the planning time from days to minutes. You’re no longer dealing with long batch cycles, and you can finally put your investments in artificial intelligence (AI) and machine learning (ML) to better use.
This speed and agility in decision-making will be a pivotal aspect to determining winners and losers in the years ahead, giving those organizations who can spin up a new scenario based on real-time market factors and execute on it in minutes the competitive edge.
While the infamous “cloud” gets talked about a lot in supply chain, it has still struggled to really get traction for a handful of reasons, most notably integration and data challenges. It’s easier said than done. Which brings us to Step 2.
Step 2: Get Your Data Together
If your data is siloed, and especially when it’s on-premises and all over the place, it’s a huge hurdle – both expensive and challenging – to get visibility across your entire supply chain. To move quickly, it’s imperative to think about how all the moving pieces of a supply chain interplay. When you make a capacity plan, you need to understand how this lines up with demand forecast, implications to your network, or what it means for warehouse staffing. It needs to all match up, or else you’re stuck in this constant back-and-forth, which results in lost time and lost profits.
And beyond simply having visibility, fragmented data results in fragmented or conflicting reporting, analytics, and insights. You don’t want your points solutions and KPIs to compete against each other. The key is bringing all your data together, creating a single source of truth for your applications and analytics. Bringing all your data onto a centralized data cloud removes the need for ETLs, mitigates the proliferation of integrations, and dramatically reduces costs of testing and ongoing maintenance. Then standardizing the data model so that all your data can be leveraged across any application, for all analytics and AI – including those you’ve invested in today and those you’ll add in the future. That’s Step 3.
Step 3: Design a Digital Transformation Plan Aligned to Your Goals
Monolith applications can take years to implement, and years before businesses see any return on their investment. You lose focus along the way. Your business model may change along the way to reflect the ever-evolving market landscape. This approach doesn’t work anymore.
Every business is at a different level of digital maturity. Some have already moved to SaaS and adopted new technologies. Some are running on older, on-premises applications. And still others have a mix of both. It doesn’t make sense – financially, technically or in terms of change management – to put every company on the same – very, very long – digital transformation path. Instead, a customer specific game plan that enables them to consume technology and innovation at their pace is key to accelerated time to value, higher return on investment, and longer-term success.
Composable microservices, which bring together specific sets of capabilities that deliver discrete sets of business values to solve specific business needs, allow organizations to break down behemoth implementations into smaller projects that can get up and running in months. This allows organizations to consume innovation that address today’s pain points right away, without waiting for other ancillary capabilities to be deployed. No more cliff events. Instead, incremental business benefits are delivered along the way.
Call out: “Best of breed” may not necessarily be “best for you.” Fragmented solutions can perpetuate siloes, and while data integrations can mask the issue, they don’t solve it. Ideally, you’re acquiring composable applications that all sit on the same platform and work synchronously together.
Step 4: Capture the Full Value of Your Data and AI
At this point, you’re on the cloud. Check. You’ve consolidated your data onto a single data cloud with a single data model. Check. And you’ve started adopting the latest functionalities and technology innovations. Check. Now it’s time to capture the full value of your data and AI. Look for ways to automate – and optimize – existing processes, leveraging the power of AI and ML. For example, Blue Yonder offers the ability to mix and match ML algorithms and AI to optimize forecast accuracy. For example, you could use two statistical models for certain SKUs and for others you, like fast-moving goods, you may apply AI. Or you could integrate your own, homegrown models as well.
By adopting Blue Yonder’s latest AI and ML, businesses realize many benefits, including an improvement in their forecast, higher fill rate, and optimized manufacturing utilization. And this operational improvement drives recurring benefits in terms of greater revenue, improved gross margin, and operating expense reductions. There are also one-time benefits associated with reduction and CAPEX avoidance.
Your Next Step: Crush Your Business Case
No CFO is willing to wait years for a return on investment. That’s why we partner with our customers. First, we sit down for a multi-day workshop and at the end provide a high-level impact and opportunity assessment. We then perform a detailed assessment over 4 to 6 weeks that identifies pain points and opportunities, the architecture that underpins it, the roadmap in the order you want to go, the sequence of events, and the detailed business case. On average our customers can achieve a 12x return on their investment.
And then the last thing we’ll provide is a change management plan, because there is a lot of change in many roles and not just roles but what people are going to be doing day to day. Together in partnership with our customers we drive this value creation.
The time to act is now. For those organizations who take the leap to the cloud, unify their data, and capture the full value of their AI, there is an enormous opportunity to capture. Those who wait risk losing their competitive edge. While no one can predict the next big disruption, it’s imperative to react with speed and agility to the day-to-day disruptions that have become the new norm.
The world is evolving, and we need to evolve along with it. By moving to the cloud, you’re well on your way. Are you ready to start your journey to supply chain resilience?