Accelerating AI Inference at Scale: Introducing Google Cloud TPU v5e
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Google Cloud’s AI-optimized infrastructure makes it possible for businesses to train, fine-tune, and run inference on state-of-the-art AI models faster, at greater scale, and at lower cost. We are excited to announce the preview of inference on Cloud TPUs. The new Cloud TPU v5e enables high-performance and cost-effective inference for a broad range AI workloads, including the latest state-of-the-art large language models (LLMs) and generative AI models.
As new models are released and AI becomes more sophisticated, businesses require more powerful and cost efficient compute options. Google is an AI-first company, so our AI-optimized infrastructure is built to deliver the global scale and performance demanded by Google products like YouTube, Gmail, Google Maps, Google Play, and Android that serve billions of users — as well as our cloud customers.
LLM and generative AI breakthroughs require vast amounts of computation to train and serve AI models. We’ve custom-designed, built, and deployed Cloud TPU v5e to cost-efficiently meet this growing computational demand.
Cloud TPU v5e is a great choice for accelerating your AI inference workloads:
- Cost Efficient: Up to 2.5x more performance per dollar and up to 1.7x lower latency for inference compared to TPU v4.
- Scalable: Eight TPU shapes support the full range of LLM and generative AI model sizes, up to 2 trillion parameters.
- Versatile: Robust AI framework and orchestration support.
In this blog, we’ll dive deeper into how you can leverage TPU v5e effectively for AI inference.
Up to 2.5x more performance per dollar and up to 1.7x lower latency for inference
Each TPU v5e chip provides up to 393 trillion int8 operations per second (TOPS), allowing complex models to make fast predictions. A TPU v5e pod consists of 256 chips networked over ultra-fast links. Each TPU v5e pod delivers up to 100 quadrillion int8 operations per second, or 100 PetaOps, of compute power.
We optimized the Cloud TPU inference software stack to take full advantage of this powerful hardware. The inference stack leverages XLA, Google’s AI compiler, which generates highly-efficient code for TPUs to maximize performance and efficiency.
The combined hardware and software optimizations, including int8 quantization, enable Cloud TPU v5e to achieve up to 2.5x greater inference performance per dollar than Cloud TPU v4 on state-of-the-art LLM and generative AI models, including Llama 2, GPT-3, and Stable Diffusion 2.1:
Google Internal Data. August 2023. Normalized to single-chip throughput. Precision: Llama 2 7B, 13B, 70B, GPT-J 6B: int8; GPT-J 175B, Stable Diffusion 2.1: bf16.
On latency, Cloud TPU v5e achieves up to 1.7x speedup compared to TPU v4:
Google Internal Data. August 2023. Precision: Llama 2 7B, 13B and 70B: int8; GPT-3 175B: bf16.
Google Cloud customers have been running inference on Cloud TPU v5e, and some have seen even greater speedups on their particular workloads.
AssemblyAI offers dozens of AI models to their customers for speech recognition and understanding with over 25 million inference calls on a daily basis.
“Cloud TPU v5e consistently delivered up to 4X greater performance per dollar than comparable solutions in the market for running inference on our production model. The Google Cloud software stack is optimized for peak performance and efficiency, taking full advantage of the TPU v5e hardware that was purpose-built for accelerating the most advanced AI and ML models. This powerful and versatile combination of hardware and software dramatically accelerated our time to solution: instead of spending weeks hand-tuning custom kernels, within hours we optimized our model to meet and exceed our inference performance targets.” – Domenic Donato, VP of Technology, AssemblyAI
Scale to the full range of LLM and Generative AI model sizes
LLMs and generative AI models continue to grow in size and computational cost. The largest models require the combined compute and memory of hundreds of hardware accelerators. Cloud TPU v5e enables inference for a wide range of model sizes. A single v5e chip can run models with up to 13B parameters. From there, you can scale up to hundreds of chips and run models with up to 2 trillion parameters.
Google Internal Data. August 2023. Batch size = 1. Multi-head attention based decoder only language models: prefix length = 2048, decode steps = 256, beam size = 32 for sampling.
Gridspace leverages Google Cloud TPU infrastructure to power its full-stack conversational AI platform – building and integrating real-time conversational ASR, LLMs, semantic search, and neural TTS.
“We’re a huge fan of Google Cloud TPUs. Our benchmarks are demonstrating a 5X increase in the speed of AI models when training and running on Google Cloud TPU v5e. We are also seeing a 6x improvement in the scale of our inference metrics. We’ve scaled our AI models to billions of conversations per year across financial services, capital markets, and healthcare with Google Cloud’s AI infrastructure. Our Grace bots are powered by models trained using Cloud TPUs and served at scale on GKE with support for PCI, HITRUST, and SOC 2 compliance.” – Wonkyum Lee, Head of Machine Learning, Gridspace
Robust AI framework and orchestration support
Leading AI frameworks, including PyTorch, JAX, and TensorFlow, provide robust support for inference on Cloud TPU v5e. This means you can now train and serve models end-to-end on Cloud TPUs: what you train is what you serve.
Google Cloud offers you many choices to run inference on Cloud TPUs easily and reliably. From GKE and Vertex AI, to popular open-source frameworks such as Ray and Slurm, you can leverage Google Cloud TPUs in your preferred way to fit your development process.
Try Cloud TPU v5e for inference today
Cloud TPU v5e provides a high-performance, cost-efficient, scalable, and reliable inference platform for LLMs and generative AI models. Leading AI companies are leveraging the power of Cloud TPU v5e to serve AI models at scale:
To get started with inference on Cloud TPU, reach out to your Google Cloud account manager or contact Google Cloud sales.
Explore The New Era of Flexibility: Streamlined AWS-to-Google Cloud Migration
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As an IT leader, you’re asked to do it all: innovate and optimize your tech stack for business outcomes — all while being secure and compliant. It takes heroic efforts to achieve innovation and progress while also tightening budgets and teams. This is why many of you are considering migrating applications to Google Cloud, for benefits like scalability and flexibility, security and compliance, disaster recovery and business continuity, and cutting-edge technologies at lower costs.
To help you do this, we suggest using Google Cloud’s Migrate to Virtual Machines – part of Migration Center. This managed cloud service lets you lift and shift workloads at scale to Google Cloud Compute Engine with minimal changes and risk.
And recently, we rolled out our latest release which introduces support for workload migration from AWS to Google Compute Engine. With this addition, you can now migrate both your on-prem and AWS workloads at scale. This means centralized management for your end to end workload migration journey from both sources via Cloud Console or APIs.
Simple and easy migrations from AWS and VMware sources to Google Cloud
Migration of AWS EC2 instances directly to Google Compute Engine using Migrate to Virtual Machines follows a well established and easy journey, which means a minimal learning curve for users who are already migrating workloads from VMware. Workload migration is agent-less, which means you do not need to access or alter workloads as a prerequisite for migration, allowing you to execute zero-touch migrations. Migrate instance data with no interruptions to the running workload at the source for a fast cutover to Google Cloud. In addition, our end-to-end cloud console interface surfaces your AWS EC2 inventory, migrations, and groups so you can execute migrations without ever leaving the cloud console interface.
Large-scale migrations
Completing a large-scale migration project in a timely manner calls for careful planning and streamlined migration sprints. The Migrate to Virtual Machines’ Groups construct enables you to group source VMs together in the planning phase. When it’s time to execute the planned migration, VM Groups let you execute migration operations on a group level, or on a subset of the group, streamlining the process at scale.
Minimal downtime and risk
Application uptime is key to keeping your business running. Every migration with this latest release of the service periodically replicates data from the source workload to the destination without manual steps or interruptions to the running workload, minimizing workload downtime and enabling fast cutover to Google Cloud. You can also launch non-disruptive migration tests — referred to as test-clones — to help you validate that these workloads will work properly in the cloud before cutting over. This helps avoid issues that might have otherwise been costly or disruptive to your business.
How the service works
Migrations simply work, at scale, in a managed service fashion. With Migrate to Virtual Machines, there’s no requirement to provision or manage migration-specific resources in the cloud. The service uses replication-based migration technology to lift and shift workloads from source environments to Google Cloud. The Migrate Connection replicates source VM disk snapshots in the background with no interruption to the source workload. Replicated data is encrypted in transit and at rest, and when you instantiate a migrating VM using a test-clone or cut-over, the service seamlessly adapts your source VM operating system to boot and run natively in the cloud — including configuring network settings and deploying Google Cloud guest packages.
The migration journey of an EC2 instance — or VMware VM — to Google Cloud is comprised of the following steps:
1. Onboarding a source VM for migration: Onboard one or more VMs for migration from the source environment fleet.
2. Configure landing zone target: You can migrate an instance to any Google Cloud project in your environment and update landing zone details at any time before executing a test-clone or cutover.
3. Initiate VM data replication of source workload: Migrate to Virtual Machines periodically replicates instance disks to the cloud with no interruption to the source instance. You can control replication frequently and pause or resume at any point in time.
4. Test migrating instance: Test-clone creates a copy of your source instance in the defined landing zone to validate the migrating instance in the cloud before executing a cut-over. You can repeat the test-clone multiple times to multiple landing zones for thorough validation
5. Cutover migrating instance: Cutover operation shuts down your source instance and then performs the short final sync to Google Cloud. Migrated VM is instantiated in the target landing zone.
Getting started with Migrate to Virtual Machines
It’s quick and easy to start migrating your AWS EC2 instances and on-premises VMs today:
- Enable the vmmigration API in a Google Cloud project
- Create an AWS source in your environment
- Onboard and initiate replication of instance data from source
- Set migrating instance target details.
- Perform non-disruptive tests of your migrating instance using test-clone
- Cutover your instance to the cloud with minimal down time
You can also visit our website to learn more about Migrate to Virtual Machines. If you know you have to migrate in 2023 but aren’t sure how to get started, you can sign up for a free discovery and assessment of your current IT landscape so we can help craft the ideal migration plan for you and your business.
Turning the Tide: How PrestaShop Regained Trust in Data
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Since 2007, PrestaShop has helped companies unlock the power of e-commerce through its open-source platform. Over 300,000 merchants worldwide use the PrestaShop platform to grow their business and serve online shoppers.
“Our open-source strategy to ecommerce enablement sets us apart,” says Rémi Paulin, Ph.D., Data Architect at PrestaShop. “Customization is becoming more crucial to retailers, and our open-source platform allows companies to continually evolve their sites and services to stand out from competitors.”
As PrestaShop grew, it wished to derive more value from its data, but the company ran into issues caused by a legacy, siloed architecture that negatively impacted data consistency and accessibility.
Let’s look at how PrestaShop works with Google Cloud and partners Fivetran and Hightouch to gain more control over data, enable a beyond-BI data strategy, and increase employee engagement from less than 10% to more than 40%.
Improving trust in data
Core systems at PrestaShop, including SQL and NoSQL databases, and SaaS Applications, were siloed; each presenting its own data, often captured from different sources such as support tickets, marketing engagement, purchase activity, and product usage. This setup made data overall inconsistent as no single system would contain a source of truth, resulting in many inefficiencies, poor collaboration across teams, and a reluctance to use data to support key decisions.
“Not long ago, less than 10% of the company regularly relied on data, so we were missing opportunities to make more data-driven decisions,” says Paulin. “Data was underutilized, and people were rapidly losing trust in data.”
PrestaShop set out to design a new architecture to address past challenges, such as lack of data consistency, and improve data accessibility.
“Google Cloud, along with Hightouch and Fivetran, allowed us to build a modern stack to solve these challenges and support our beyond-BI data strategy.”
Building a modern data stack
The first step was to build a robust data ingestion pipeline. After considering several vendors, PrestaShop chose to work with Fivetran to extract data from SaaS applications, including Zendesk, HubSpot, and GitHub, to load into BigQuery. They also use Datastream to stream Change Data Capture (CDC) data from transactional databases into BigQuery in real-time.
“Fivetran and Datastream are no-ops, efficient and highly reliable, and relieve our Data Engineers of management tasks. This brings us a high degree of confidence to build the rest of the stack atop these services,” says Paulin.
PrestaShop relies on several Google Cloud solutions, including Dataflow, and a managed Spark service by Ascend.io, for data transformation. It also uses Looker for its semantic modeling capacities and as a self-serve data platform.
As the company continued on its journey to transform how it manages and benefits from data, it engaged Hightouch to enable data accessibility through activation. Sitting on top of Looker, Hightouch unlocks all data models for operational intelligence. For example, in just a few days, the team built a customer knowledge model combining data from multiple sources and used Hightouch to sync data from the semantic layer to Zendesk via Reverse ETL. This allowed the care team to make more data-informed decisions, speeding up the time to resolve support tickets submitted through Zendesk by 33%.
“Hightouch feels like a natural extension of Looker and reinforces the position of the semantic data model as the single source of truth,” says Paulin. “It powers a variety of Data Activation use cases, supporting our beyond-BI strategy by providing teams with access to data when and where they need it to improve everyday operations. This has a big impact on the company, bolstering employee trust in available data.”
Becoming data-driven
In less than six months, PrestaShop managed to get the entire data stack up and running, build over 30 data models and engage over 120 employees with a small team of only two Data Engineers.
“Data is now accessible to every stakeholder within the company, regardless of their technical abilities,” says Paulin.
PrestaShop has already seen much progress in its shift to a more data-driven company and is excited to roll out more self-service intelligence capabilities in the future.
“Google Cloud drives home a culture of simplicity around our data stack, which is essential for us, especially given the small size of our engineering team,” says Paulin. “Fivetran and Hightouch share this culture of simplicity. Together, they offer strong foundations to support our data needs.”
Dashboards, which the company had always had an appetite for, are seamlessly created today. Before moving to Looker, a full-fledged dashboard would take an average of six weeks to develop. Now, it takes less than two days – and a simple dashboard can be created autonomously by business users in as little as 15 minutes.
Furthermore, data usage goes beyond dashboards. Thanks to Looker’s self-service exploration capabilities, many stakeholders can now glean insights surrounding product issues and business opportunities. Thanks to Hightouch, teams can activate their data to make better and smarter operational decisions.
“This is a big leap forward and one of many to come as we continue to add new models, activate our data, and onboard more users,” says Paulin. “Given our global reach and unique approach to e-commerce enablement, we know this is just the start of the great things we can accomplish with Google Cloud, Fivetran, and Hightouch.”
Check out Fivetran on Google Cloud Marketplace, or sign up for a free Hightouch workspace to learn more about what partners can do for your business.
Built on Google Cloud, Enexor’s Bio-CHP Unit Powers 100 Homes with Renewable Energy!
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Editor’s note: Earth Day reminds us that we all can contribute to creating a cleaner, healthier, and more sustainable future. Google Cloud is excited to celebrate innovative startup companies developing new technology and driving sustainable change. On this year’s Earth Day we’re highlighting Enexor BioEnergy and their initiative to produce clean, sustainable energy from plastic and agro-waste with the help of Google Cloud solutions.
Picture a world without electricity where billions of people burn dangerous fuels and trash from landfills to cook meals and heat their homes. Children constantly cough, choking on toxic smoke that lingers in houses and sickens entire families. Because there are no pumps or purification plants, contaminated water is hauled in buckets from dirty rivers and polluted wells. Without power or lights, hospitals and emergency medical clinics can only provide basic services during the day.
Although it is 2022, this harsh life is a reality for billions of people living in developing countries around the world.
Producing clean energy from plastics and organic-waste
This Earth Day, let’s imagine what life would be like in these countries if people had access to safe and inexpensive bioenergy. In this world, indoor air is fresher. Clean water runs from faucets, while homes, businesses, and schools have electricity. Doctors and nurses have the power to treat patients 24 hours a day and save lives with advanced medical equipment. Local economies boom and entrepreneurs thrive.
This is the sustainable future Enexor BioEnergy and its partners are building—one village at a time. With the Enexor Bio-CHP™ system, we produce clean and sustainable energy from discarded plastics, organic, and biomass-waste such as rice and corn husks, seaweed, coconuts, and other biomatter while offsetting significant Carbon emissions. The Bio-CHP can be commissioned and easily installed in just a single day, with multiple systems installed side-by-side when more power is needed. By being offered under its novel Energy-as-a-Service business model, Enexor ensures that the Bio-CHP can generate immediate environmental positive impact and customer adoption.
Each Bio-CHP unit generates enough energy to power over 100 homes—and provides much-needed renewable electricity and thermal power for schools, businesses, manufacturing facilities, water pumps, Wi-Fi systems, and telecommunications towers. The Bio-CHP creates clean energy by safely oxidizing plastics and biomatter in a secure container using a high-temperature system to power a micro-turbine. This produces bioenergy, significantly reducing harmful greenhouse gas emissions.
By solving a community’s waste issues while providing more affordable renewable energy, the Bio-CHP also creates new economic opportunities and improved outcomes where it is installed. This includes using its inexpensive power to expand local services and offerings, and empowering local community clean up efforts by incentivizing waste collection via blockchain-enabled digital currencies and services such as PayGo. Additionally, the Bio-CHP is an ideal solution for businesses who desire to maximize their own sustainability efforts, gain greater energy resiliency, and save money on their current energy and waste costs.
Engaging in Google for Startups Accelerator: Climate Change
When developing the Bio-CHP, we realized we needed a reliable and experienced partner to help us incorporate the best in class machine learning and artificial intelligence into our technology. That’s why we joined the Google for Startups Accelerator and participated in the Google for Startups Accelerator: Climate Change.
The accelerator introduced us to other companies working to create a sustainable future and opened new opportunities for collaboration and partnerships. The accelerator also continues to give our small team access to the best of Google Cloud’s people, programs, and solutions. We especially want to highlight Google Cloud’s dedicated startup experts and the incredible technical support they provide, as well as the Google Cloud research credits we used to explore new solutions.
As an example, Enexor is developing a predictive maintenance tool that automatically adjusts Bio-CHP operations to match fuel composition. Another tool in development proactively identifies and flags potential Bio-CHP system and component failures—before they occur.
Google Cloud’s dedicated startup experts work closely with Enexor to develop predictive models for these tools and Enexor also used the Google Cloud research credits that were provided to build these advanced models on TensorFlow, Vertex AI, Cloud CDN and AutoML. Since each system is remotely monitored from Enexor’s global headquarters in Tennessee, predictive maintenance tools also increase the safety, reliability, and efficiency of Bio-CHP in off-grid locations.
Generating 13 billion kWh of clean power by 2040
In the future, Enexor plans to explore additional Google Cloud solutions such as BigQuery to crunch larger datasets, Google Data Studio to build dashboards, and perhaps even Google Cloud Tensor Processing Units (TPUs) to more efficiently process machine learning (ML) workloads.
These solutions will help Enexor to achieve three primary goals by 2040: to generate 13 billion kWh of clean power, reduce 120 million tons of CO₂, and provide one million people with access to clean and sustainable energy. With each Bio-CHP system, Enexor annually reduces up to 2,000 metric tons of CO₂ equivalent emissions by decreasing methane emissions released from landfills, offsetting fossil fuel-based power generation with carbon credits and minimizing waste disposal transportation emissions.
Enexor is now preparing to deploy the Bio-CHP in Accra, Ghana where it will convert organic and plastic manufacturing waste into sustainable energy. Enexor is also looking forward to working with the local Accra community and NGOs to collect discarded plastics and organic waste diverting it from ending in the rivers and oceans and instead using them as renewable fuel sources. We can’t wait to see what we accomplish next as we celebrate Earth Day 2022 and think about the sustainable future Enexor is helping to empower.
If you want to learn more about how Google Cloud can help your startup, visit our page here to get more information about our program, and sign up for our communications to get a look at our community activities, digital events, special offers, and more.
Google and NetApp Partnership Expansion to Ease Customers’ Cloud Migration
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As organizations continue to evolve to meet the needs of their stakeholders, they are increasingly looking to adopt the cloud and digitally transform their business. Since our partnership with NetApp began in 2018, we’ve been focused on delivering the infrastructure, tools, and services to help customers on their cloud migration journey and benefit from their data to better serve their customers.
“Customers are looking to adopt flexible and scalable solutions that meet the needs of their business,” said Ronen Schwartz, SVP & GM, Cloud Volumes, NetApp. “Our long-standing partnership with Google Cloud continues to deliver innovative solutions for customers as they look to migrate and run their business critical applications in the cloud while unlocking the power of their data with industry-leading cloud services.”
Innovative, industry-first solutions have become the standard for our partnership. From the general availability of NetApp Cloud Volumes Service (CVS) for Google Cloud in 2019, to our collaboration on new architectures in 2020 with the release of the software-defined CVS powered by Google Kubernetes Engine (GKE), we continue to deliver first-of-its-kind enterprise file storage services together. In 2021, the pace of innovation has only increased—together, we delivered volume replication powered by SnapMirror, which efficiently copies volume data from one Google Cloud region to another for data consistency, development, testing, or disaster recovery.
We’ve also made our services available globally—you can now run Cloud Volumes ONTAP in all 28 Google Cloud regions, and CVS is now available in 19 regions, allowing you to access our services wherever you are around the globe. All of this is backed up by a 99.99% SLA for CVS, enabling high availability for your enterprise workloads.
Hundreds of customers including MailerLite, a leader in marketing automation, have benefitted from our joint services. MailerLite was looking to move millions of files to the cloud without disruption as they were facing availability, management, and maintenance challenges as their business scaled. By leveraging NetApp CVS on Google Cloud, MailerLite was able to migrate over 100 million files to Google Cloud in about an hour, removing their ongoing infrastructure overhead, saving developer hours, and eliminating the scalability limitations they previously experienced.
Expanding our partnership
Last week at Google Cloud Next ‘21, we announced we are expanding our strategic partnership in two ways to make it even easier for customers to migrate and run business critical applications on Google Cloud. First, NetApp will provide storage infrastructure for the newly announced Google Distributed Cloud Hosted, where data resides in customer-owned data centers and colocation facilities. This enables a safe and secure way to modernize an on-premises deployment while still meeting data security and privacy requirements.
Additionally, for customers looking to migrate their VMware workloads to Google Cloud, we announced preview access for NetApp Cloud Volumes as datastores for Google Cloud VMware Engine. By providing customers with the choice to scale compute and storage independently, customers can now reduce costs and complexity when migrating and running storage-bound workloads. This also allows customers to address regional disaster recovery use cases, making it easier and more cost-effective to move on-premises workloads into Google Cloud. To get started, you can sign up for preview access using the Registration for Preview Access form.
Looking forward
We’re excited for what’s to come with our partnership and committed to delivering value to customers across industries. Google Cloud is a Gold sponsor at this week’s NetApp Insight, and we invite you to join our spotlight session featuring Google Cloud and NetApp leaders. Additionally, we are leading multiple breakout sessions where you will hear from our product team on how you can accelerate cloud adoption with Google Cloud and NetApp. You can also learn more and get started today by visiting our NetApp on Google Cloud website.
If You Run Your Country’s Largest Retail Franchise, How Do You Pull Together, in Sync?
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In 1984, Mario Maio set up a small business manufacturing electrical transformers in his Johannesburg garage. Over the next two decades, the ACDC Dynamics company he created came to dominate manufacturing, import, and distribution in South Africa’s electrical goods sector. Then, in 2007, Mario’s son, Ricardo Maio, founded a retail arm to the business, ACDC Express. Today ACDC Express is South Africa’s largest electrical retail franchise, with 29 franchise stores across the country. Eight of those franchises joined in 2017 alone, and ACDC Express is experiencing quarter-on-quarter growth of 28% per year.
Rapid expansion increases the demands on the ACDC Express central administration, which provides each franchise with IT support and a full suite of marketing, operational, and bookkeeping functions. So when email server downtime became a frequent problem, Ricardo and his team chose G Suite to transform the way the franchise worked.
“We lost revenue when our email servers went down. When I researched Google’s SLA of 99.9% uptime and experimented with G Suite on my private Gmail account, I could see the difference this technology could create.”
Ricardo Maio, CEO, ACDC Express
“On consecutive occasions, our entire email server went down,” says Ricardo Maio, CEO at ACDC Express. “It would take more than one or two days to bring it back up. We had already highlighted software cost overhead as a potential thing to reduce, so when that happened several times within a short period, we knew it was time to make a change.”
Building a better franchise
Franchise businesses undergoing rapid expansion must respond quickly to the demands of new stores. At ACDC Express, 33 staff run the national franchise, delivering core services and support to 29 franchises across the country. Key tasks, such as updating the operations manual, were hampered by a reliance on paper forms and mail services, while email servers experienced repeat failures, which compromised communication. By implementing new, cloud-based productivity tools, ACDC Express looked to cut down on slow and expensive practises, and deliver an agile, reliable online communications platform.
To do that, ACDC Express migrated its franchise to G Suite with Opennetworks. “We lost revenue when our email servers went down,” says Ricardo. “When I researched Google’s SLA of 99.9% uptime and experimented with G Suite on my private Gmail account, I could see the difference this technology could create.”
Since moving to Gmail, ACDC Express reports that the problem of email server downtime “is no longer existent for us,” while with Google Drive, versioning problems have been resolved. Using surveys on Google Forms, ACDC Express quickly and easily collects data from stores and customers—whether they are in stores or on the road—and populates Google Sheets with the information.
“Our operations manual is a binding document, and it’s a living document that gets regularly updated. In the past, we would struggle to track which franchise had which version. With Google Drive, we can be sure that everyone is looking at the right one.”
Ricardo Maio, CEO, ACDC Express
With Google Data Studio, the managing team then consolidates that data on dashboards, creating snapshots of performance, complete with averages and simple comparisons, which make it easy to spot issues and outliers in need of attention. Individual businesses that do require help are then contacted over Google Hangouts Meet to assess what they need, part of a culture of sharing expertise, which Ricardo sees as key to the franchise mode.
“As a franchise, sharing knowledge is as important as maintaining control,” he says. “If there’s a new procedure or system that worked in one store, we can immediately update our manuals and documentation so that everyone has access to it. That’s been fantastic.”
“Our operations manual is a binding document, and it’s a living document, which gets regularly updated,” says Ricardo. “In the past, we would struggle to track which franchise had which version, and every time we had to make a change we would print out a version and send it to stores through an unreliable postal service. With Google Drive, we can be sure that everyone is looking at the right one.”
Remote training, rapid migration
Rolling out new IT tools across a franchise is often expensive, demanding extensive travel and numerous training sessions, which often repeat the same material. Instead, ACDC Express set up training on Google Hangouts that staff could drop into at their convenience, creating a cost-effective training schedule, which meant individual stores could plan their own learning process.
“When we moved to G Suite, we did it all at once, with every employee changing at the same time. We took a band-aid approach, switching to the new tools as rapidly as possible. After six months of training, there have been no reported problems with G Suite at all.”
Ricardo Maio, CEO, ACDC Express
“The whole benefit of franchising is that you can learn from your peers,” says Ricardo. “When we moved to G Suite, we did it all at once, with every employee changing at the same time. We took a band-aid approach, switching to the new tools as rapidly as possible. After six months of training, there have been no reported problems with G Suite at all.”
More mobile, more reliable
Today, ACDC Express operates 240 Google accounts, and information from the franchises’ marketing systems, research, operations, and accounting is fed back automatically to Google Sheets and Google Dashboard at the headquarters in Edenvale, Gauteng. By Ricardo’s estimation, the administrative team is now so effective with G Suite tools, it can achieve twice as much as it could without them.
Now, ACDC Express is looking to use Google Chromebooks in a new web-based point-of-sale system, and considering moving its ERP onto Google Cloud Platform for greater stability, in another project with Opennetworks.
“We’ve developed an in-house point of sale system that’s web-based and can use a functional touchscreen,” adds Ricardo. “We’re looking at rolling that out with Google Chromebooks. We really like how straightforward and simple the Google Chrome devices are, and because we’ve taken a lot of infrastructure into the cloud, we no longer actually need physical machines on our counters. We can work anywhere. That’s something that applies from our head office right down to our smallest franchise store.”
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