Responding to multiple, simultaneous disruptive forces has become a daily routine for most demand planners. To effectively forecast demand, they need to be able to predict the unpredictable while accounting for diverse and sometimes competing factors, including:

• Labor and materials shortages
• Global health crises
• Shifting cross-border restrictions
• Unprecedented weather impacts
• A deepening focus on sustainability
• Rising inflation

Innovators are looking to improve demand forecast accuracy by incorporating advanced capabilities for AI and data analytics, which also speed up demand planning. According to a McKinsey survey of dozens of supply chain executives, 90% expect to overhaul planning IT within the next five years, and 80% expect to or already use AI and machine learning in planning.

Google Cloud and SAP have partnered to help customers navigate these challenges and supply chain disruptions starting with the upstream demand planning process, focusing on improving forecast accuracy and speed through integrated, engineered solutions. The partnership is enabling demand planners who use SAP IBP for Supply Chain in conjunction with Google Cloud services to access a growing repository of third-party contextual data for their forecasting, as well use an AI-driven methodology that streamlines workflows and improves forecast accuracy. Let’s take a closer look at these capabilities.

Unify data from SAP software with unique Google data signals

When it comes to demand forecasting and planning, the more high-quality and relevant contextual data you use, the better, because it helps you understand the influencing factors of your product sales to sense trends and react to disruptions or capitalize on market opportunities more timely and accurately.

The expanded Google Cloud and SAP partnership helps customers who use SAP® Integrated Business Planning for Supply Chain (SAP IBP for Supply Chain) bring public and commercial data sets that Google Cloud offers into their own instances of SAP IBP and include them in their demand planning models in SAP IBP. So, in addition to sales history, promotions, stakeholder inputs and customer data that are typically in SAP IBP, a demand planner can incorporate their advertising performance, online search, consumer trends, community health data, and many more data signals from Google Cloud when working through demand scenarios.

More data enables more robust and accurate planning, so Google continues to build an ecosystem of data providers and grow the number of available data sets on Google Cloud. Some current providers include the U.S. Census Bureau, the National Oceanic and Atmospheric Administration, and Google Earth, and partnerships are underway with Crux, Climate Engine, Craft, and Dun & Bradstreet to help companies identify and mitigate risk and build resilient supply chains.

Augmenting demand planning with additional external causal factor data is a starting point to drive more accurate forecasting. For example, knowing what regional events may be happening, or the weather patterns that may impact sales of your products, allows you to react faster to these changes by making sure adequate supply is being provided. The result is a more accurate overall plan that reduces resource waste and out-of-stock events. Planners can respond with more accurate and granular daily predictions about sales, pricing, sourcing, production, inventory, logistics, marketing, advertising, and more based on the expanded data.

Get more accurate forecasts with Google AI inside

Extending the already expansive algorithm selection available in SAP IBP, the release of version 2205 allows SAP IBP customers to access Google Cloud’s supply chain forecasting engine, which is built on Vertex AI — Google Cloud’s AI-as-a-platform offering — from within SAP IBP as part of their forecasting process.

The benefit of using an AI-driven engine for demand forecasting is that it meaningfully improves forecast accuracy. Most demand forecasting today is done through a manually set, rules-based model versus an AI-driven model that is smarter and gets better at predicting demand as it works.

Take the fastest path from data to value with streamlined workflows

Vertex AI can include relevant contextual data sets for demand planning, and the results can be shown in SAP IBP for planners to incorporate when building their workflows.

In addition to more accurate forecasts, planners can work faster and more efficiently as they build potential scenarios, meaning they can do more simulations than they do now so that a wider range of disruptions can be modeled. Customers of SAP IBP don’t have to do any of the heavy lifting. They just have to share their data from SAP IBP with Google, then access the process workflow capabilities to set up automated workflows that use the combined data. Google makes the data available so that planners can use it as they’re setting up their workflows in Vertex AI.

Users of the Google Supply Chain twin and SAP IBP can combine the rich planning data from IBP with additional SAP data and other Google data sources to provide better supply chain visibility. The Google Supply Chain twin is a real-time digital representation of your supply chain based on sales history, open customer orders, past and future promotions, pricing and competitor insights, consumer history signals, external data signals and Google data.

Leverage Google data signals with SAP IBP for more accurate forecasts

It’s not difficult to access these new capabilities, and the benefits are more accurate near-term forecasts and more return on your investments in SAP IBP and Google Cloud. If you happen to be at the Gartner Supply Chain Symposium from June 6-8th in Orlando, Florida, stop by our booth to say hello. Or, get started now

High Performance Computing (HPC) is prevalent today across many industries, including financial services, life sciences, higher education research, manufacturing, and energy. More and more businesses are deploying HPC workloads in the cloud to take advantage of its elasticity, scalability, and availability. Job schedulers are critical for HPC applications given the nature of these workloads that create, process, and tear down thousands, and sometimes millions, of vCPU and network resources with TB to PB of storage capacity. Job scheduling tools lead to improved operational efficiency and a degree of certainty that a particular HPC job, which can run for hours to weeks, will complete successfully. 

IBM Spectrum LSF is used extensively in the manufacturing and semiconductor industry to manage Electronic Design Automation (EDA) workloads. Dynamically running workloads on-premises and in the cloud, also known as cloud bursting, is becoming a more common practice to address capacity and provisioning time constraints within data centers and enable enterprises to take advantage of virtually unlimited resources. 

However, the challenge with cloud bursting is integrating and maintaining operational consistency across on-premises and cloud environments. IBM Spectrum LSF, in combination with Google Cloud, addresses this problem head on. 

Google Cloud is excited to announce, in collaboration with IBM, enhanced capabilities to IBM Spectrum LSF that enables organizations to integrate their on-premises job scheduling scripts with resources deployed in Google Cloud. Customers are now able to fully leverage Google Cloud’s highly scalable and secure Compute Engine, networking and storage infrastructure. 

The LSF-Google Cloud resource connector patch supports key Google Cloud differentiators including Local SSDs, GCE instance templates, Preemptible VMs, and more: 

• Bulk API support– Deploy large fleets of VM instances in a matter of seconds.
• Instance Templates – Simplify VM configuration by creating reusable templates. 
• All Machine Types – Supports all GCE VM families and machine types, including Custom Machine Types.
• GPUs – Attach up to 16 GPUs per instance, including the largest A2 instances with up to 16 NVIDIA A100 GPUs
• Preemptible VMs – Preemptible VMs are provisioned from excess Compute Engine capacity and is a significant way to save money on GCE resources.
• Local SSD – Attach up to 9TB of NVMe SSD per instance
• Hyperthreading – Supports the “threads-per-core” option in GCE, which allows per-VM hypervisor level Hyperthread configuration (when supported by Instance Templates)
• Images – Supports custom disk images, including full support for Windows, for all attached Persistent Disks
• Placement Policies – Control where the instances are physically located relative to each other within a zone for improved low-latency performance
• Labels – Supports GCE Labels, which can be used for management of firewall rules, tracking billing, etc
• Minimum CPU Platform – Supports the ability to specify a minimum CPU Platform for your Virtual Machines.

Getting Started

This improvement to the IBM LSF Resource Connector was developed by IBM in coordination with Google. Find out more about the new supported features and their operation in the official IBM Spectrum LSF Resource Connector Documentation. You can also find additional documentation and download the software in the IBM Spectrum Computing Community. If you have further questions, you can contact IBM, or Google Cloud Sales.

Special thanks to Annie Ma-Weaver, Mark Mims, and Wyatt Gorman for their contributions.

Editor’s note: This article first appeared in Consumer Goods Technology Magazine

Shifting work habits, more online shopping options, rising inflation, and stretched supply chains are just a few factors making it harder to discern what’s top-of-mind for shoppers today.

But we’re starting to get a clearer picture of what consumers say they value most right now. New Harris Poll research commissioned by Google Cloud reveals how U.S. shoppers are thinking about consumer goods brands in new ways—from apparel, electronics, and beauty products, to food and beverage.

While price unsurprisingly continues to be a major consideration in purchases, the average shopper is increasingly paying close attention to the values of consumer goods brands and how eco-friendly their products and practices are.

Shoppers want to buy from brands aligned with their values

COVID-19 drove people to reflect on their priorities, elevating concepts like community service, equity, and sustainability. A decade ago, most consumer goods companies would not have made these front-and-center, operational priorities. But today’s consumer not only wants savings and convenience, they also want that good feeling that comes from spending their money with a company that aligns with their values.

Our new research reveals that 82% of shoppers prefer a consumer brand’s values to align with their own, and they’ll vote with their wallet if they don’t feel a match. Three-quarters of shoppers reported parting ways with a brand over a conflict in values.

Even with their favorite consumer goods products, a majority of shoppers will not compromise on principles. If there’s a value mismatch, 39% of shoppers said they’d permanently boycott their favorite brand, and 24% would break ties at least temporarily. Most won’t be quiet about their concerns either: 28% of consumers that found their values at odds with a brand said they have shared their concerns with friends and family, and another 15% have shared their qualms on social media.

Consumer goods companies need to prioritize sustainability

A majority of today’s consumers (52%) are especially interested in supporting sustainable brands. They want to know how companies are managing their resources, specifically whether they are sourcing responsibly. These shoppers want to see meaningful, measurable efforts from CPG firms to save energy and reduce waste, like how Nuuly, URBN’s digital rental and resale business, has woven sustainability into its business operations, from its distribution centers to reusable packaging.

In fact, 66% of shoppers are now seeking out eco-friendly brands, with 55% saying they would pay more for more sustainable products. But these same shoppers are skeptical too: 72% think that companies and brands overstate their sustainability efforts. And they’re right to question brands’ practical application of their values. According to another Harris Poll survey recently commissioned by Google Cloud, 58% of executives polled across 16 countries admit that their organization has overstated its sustainability efforts.

Product availability is table stakes

A final point from the research: The global supply chain has stretched past its limits, and 60% of consumers are voicing some level of concern about it. At the end of the day, if a preferred brand isn’t actually on the shelves of a real or digital store, it doesn’t matter what the brand’s values or sustainability efforts are. A staggering 98% said they’d either buy from a different brand or search other stores or websites.

What’s a brand to do?

After more than 25 years working in the consumer goods industry in roles ranging from marketing and product development to business strategy and technology, at companies like Johnson & Johnson, Kimberly Clark, Carter’s, and now Google Cloud, I’ve seen successful brands do four things well when it comes to their values:

1. Don’t be generic.
   Your brand’s values need to be authentic, and they need to have teeth. But being too bold could run the risk of alienating some consumer segments. This is where technology can help. Personalizing your messages and outreach to specific shopper profiles is one way to ensure that your core values reach the right customers at the right time.
2. Make your values clear and consistent.
   When focusing on which values to highlight with your consumers and the world, make sure they make sense for your brand and that you’ll stick to them over time. For example, it’s painfully obvious when a brand is being opportunistic and inserting itself into conversations around values like sustainability or social justice, when it doesn’t have a history of voicing those values. The key to clear and consistent messaging of values is balancing authenticity with relatability and the appropriate amount of promotion.
3. Develop sustainability practices and communicate their impact to everyday people.
   How everyday people perceive a consumer goods brand’s sustainability initiatives is different from how an investor or general business audience does. Shoppers don’t read business sustainability plans or impact reports. To increase awareness of your brand’s sustainability efforts, consumers need to identify and interact with your brand and products directly. Some of my favorite examples are how I love that Google Maps gives me the choice of eco-friendly driving directions, and that I know I can buy low-waste, packaging-free cosmetics from a company like Lush.
4. Reward customer loyalty.
   Shoppers have more choices than ever before, and supply chain woes are testing preferences even further. But when someone chooses a specific brand because they feel aligned with their values or like their eco-friendly products, that shopper doesn’t always get recognized or thanked. Implementing a rewards program or following-up with customers after their purchases is one way you can make loyal shoppers feel appreciated while creating a lasting relationship that extends as long as possible.

As an enterprise admin, when you choose to use Google Cloud Private Catalog to enable curated, self-serve Google Cloud infrastructure provisioning, you need the ability to manage your organization’s deployments. Today, we’re pleased to announce support for several improvements to Terraform driven deployments through Private Catalog. 

With this new release, you can update Terraform configurations and keep your end users informed about updates. At the same time, Private Catalog users have the ability to view new updates, note version highlights and then update the deployment. This gives you greater control over managing deployments for solutions provisioned through Private Catalog and ensuring compliance with organizational policies and standards.

Let’s take a closer look at the features you’ll find in this release. 

Deployment change management

Terraform solutions use Cloud Storage’s Object Versioning to manage updates to configuration files. With this release, you may update configuration files using multiple approaches.

• Update the solution’s Cloud Storage object with a new configuration version
• Use a different Cloud Storage object that contains a new configuration file

Once you view and apply the changes to the solution in a Private Catalog, end users are immediately able to consume the new version of the deployment configuration.

Additionally, prior to applying any changes, you can evaluate the contents of an update by comparing versions to download and compare the current and latest versions of the configuration and use new version highlights to add a description about the updates.

Ease of consumption

Once Private Catalog detects a change to the deployment configuration, it automatically informs catalog users about the change. On the Solutions page, end users have the ability to:

• Get informed about solutions that have updates
• View version highlights published by the admin
• Apply the new version 

Additionally, with this release, Catalog users can retry existing deployments by modifying deployment parameters.

Reporting improvements

The deployment reporting dashboards for Private Catalog-based deployments now show additional information about the version of a solution deployed. This enables deeper insights into the overall deployment status across all Private Catalog solution assets.

Get started today

These new features are available to all Private Catalog customers. To learn how to use these features, refer to our documentation:

• Create a Terraform configuration in Private Catalog
• Manage and update your Terraform configurations in Private Catalog