Accenture and Google Cloud Bring AGBG to Indonesia

On September 5, 2019, Accenture and Google Cloud announced the strategic expansion of the Accenture Google Cloud Business Group (AGBG) into Indonesia. The move was aimed at helping Indonesian enterprises modernize their IT infrastructure and accelerate adoption of cloud technologies by combining Accenture’s industry consulting expertise with Google Cloud’s platform capabilities.

The expansion was driven in part by Indonesia’s rapidly growing middle class, which both organizations identified as a significant opportunity for businesses investing in digital transformation, customer experience, and data-driven services.

Why Indonesia? The Middle Class Growth Opportunity

According to Accenture research titled “Pivoting to the Future”, a majority of companies surveyed in Indonesia agreed that technology is the primary driver of innovation, and many planned to migrate their infrastructure to the cloud. The research also indicated that Indonesian companies preferred leveraging new technologies to grow their existing customer bases rather than solely acquiring new ones.

“Indonesia’s growing middle class consumers is the main reason for this expansion to Indonesia,” said Seong Kim Ho, Country Managing Director for Accenture in Indonesia. “We would like to help clients enable multi-channel customer interactions and improve access to self-service and issue resolution capabilities, while decreasing the cost to service each customer.”

Three Core Focus Areas for Indonesian Enterprises

The AGBG partnership in Indonesia targets three primary areas of enterprise transformation:

• Multi-channel customer interactions: Enabling seamless engagement across voice and digital channels, including AI-powered contact centre capabilities.
• Data management improvement: Helping organisations consolidate and govern enterprise data to derive actionable insights.
• Hyper-personalisation: Building tailored marketing, sales and service experiences by combining Google Marketing Platform data with other enterprise data sources.

A key technology underpinning the customer interaction work is Accenture’s Contact Center AI (CCAI) solution, which leverages Google Cloud’s AI and machine learning capabilities to enable end-to-end customer interaction across both voice and digital channels.

Industry Priorities: Retail, CPG, and Health

AGBG’s initial industry focus in Indonesia centres on retail, consumer packaged goods (CPG), and healthcare. Within these sectors, the collaboration targets several specific capability areas:

• AI and ML-driven business processes: Building next-generation workflows that use artificial intelligence and machine learning to create new enterprise value.
• Cloud infrastructure modernisation: Migrating workloads to Google Cloud and providing managed services tailored to the platform.
• Managed SAP on Google Cloud Platform (GCP): Delivering managed SAP solutions for clients running SAP workloads, bringing global scale to GCP-hosted SAP environments.
• Customer experience through data integration: Combining Google Marketing Platform data with enterprise data sources to generate deeper customer insights and drive engagement.
• G Suite enterprise rollout: Scaling Google’s cloud-native productivity platform (G Suite) across organisations to modernise collaboration and workforce tooling.

SAP Migration Example: BBVA Seguros

One concrete example cited at the time of the announcement was BBVA Seguros, where Accenture was implementing an SAP S/4HANA migration to Google Cloud. The stated goals of that engagement included leveraging GCP’s infrastructure performance, taking advantage of consumption-based pay-per-second pricing, and enabling innovation at scale to support BBVA Seguros’s business model transformation.

Accenture Google Cloud Center of Excellence

As part of the Indonesia expansion, the AGBG partnership planned to launch an Accenture Google Cloud Center of Excellence. The centre was intended to develop solutions in high-growth areas, accelerate client adoption of Google Cloud, and bring in global talent to build capabilities within the local Indonesian workforce.

“AGBG combines Accenture’s extensive industry knowledge with the power of Google Cloud technology to help our customers in Indonesia solve complex technology challenges and explore new business models in a digital era,” said Tim Synan, Regional Director, Google Cloud in Southeast Asia.

Practitioner Scale and Training

At the time of the announcement, Accenture reported approximately 1,000 practitioners trained on Google Cloud technologies and stated its intention to more than double that number during fiscal year 2019 (FY19).

Context: What the AGBG Partnership Means for DevOps and Cloud Teams

For engineering and DevOps teams working within large Indonesian enterprises, this type of SI-hyperscaler partnership typically translates into structured migration pathways, pre-built reference architectures, and access to certified practitioners who can accelerate time-to-cloud. Key practical takeaways from this kind of partnership announcement include:

• Managed service offerings often reduce the operational burden on internal teams during initial cloud migrations.
• Centers of Excellence can provide internal teams with training resources, best practices documentation, and architecture review support.
• SAP-on-GCP engagements are complex multi-year programmes; consumption-based pricing models can meaningfully affect total cost of ownership calculations versus on-premises licensing.
• AI-assisted contact centre tooling (such as CCAI) integrates with existing telephony stacks, but typically requires data pipeline work to connect voice data with CRM and analytics platforms.

This article is based on the original PRNewswire press release issued on September 5, 2019, as reported by finance.yahoo.com.

CI/CD vs Continuous Deployment: More Than Just Initials

These three terms are closely related but serve different purposes in the software delivery lifecycle. Conflating them leads to poor tooling choices and unrealistic expectations.

Continuous Integration (CI)

Continuous integration is a development practice in which every developer merges code into a shared repository multiple times per day. Each merge triggers an automated build and test run, giving the team fast feedback on integration problems. When a team is working on multiple features simultaneously, frequent integration surfaces conflicts early — dramatically reducing the debugging time needed to find the root cause of a broken build.

Continuous Delivery (CD)

Continuous delivery extends CI by ensuring that every successful build is in a state that could be released to production at any time. The key word is “could”: a human gate or approval step still controls whether a build is actually promoted to production. This distinction matters because not every team is ready — culturally or technically — to push every green build straight to users.

Continuous Deployment

Continuous deployment goes one step further: every build that passes the automated test suite is automatically released to the production environment without manual intervention. The human gate is removed entirely. This is the most advanced stage of the pipeline and the one that delivers the greatest competitive advantage — provided the automated test coverage and rollback mechanisms are mature enough to support it.

Why Continuous Deployment Is Worth the Investment

Combining CI, CD, and continuous deployment into an end-to-end pipeline creates visibility across the entire software delivery process and tightens the feedback loop between development and operations. No two pipelines are identical — each organisation has its own governance, compliance requirements, and release cadences to accommodate — but the core benefits are broadly consistent.

• Developer time redirected to product work. Automating build, test, and deployment steps removes repetitive manual tasks from the developer workflow. Freed from toil, engineers spend more time on features, performance work, and technical debt reduction.
• Higher reliability and fewer human errors. Manual deployment steps are a common source of production incidents. Scripted, automated pipelines execute the same way every time, reducing configuration drift and operator error.
• Faster bug resolution. When the pipeline runs on every commit, regressions are caught close to when they were introduced. Finding a bug the same day it was written is orders of magnitude cheaper than finding it a week later in a release branch.
• Competitive release velocity. Teams that ship continuously respond to customer feedback and market changes faster than teams shipping on monthly or quarterly cycles. In fast-moving markets, that cadence is itself a competitive differentiator.
• Talent attraction and retention. Skilled engineers gravitate toward teams with mature engineering practices. A well-documented, well-maintained pipeline signals that a team values developer experience and sustainable ways of working.

Build vs Buy: Why You Should Not Roll Your Own Pipeline Tools

Unless your product is CI/CD tooling, you should almost certainly not build your own pipeline infrastructure from scratch. The same reasoning that leads organisations to use managed email services rather than operating their own mail servers applies here. Purpose-built, commercially supported (or well-maintained open-source) CI/CD tools provide battle-tested reliability, plugin ecosystems, and active security patching that an in-house tool rarely matches.

Investing in proven, configurable tooling frees your engineers to solve your actual business problems. The overhead of maintaining a homegrown pipeline quickly becomes a distraction that slows the very delivery it was meant to accelerate.

Release Automation and Release Orchestration

Two complementary capabilities underpin a mature continuous deployment pipeline:

Release Automation

Release automation handles the packaging and deployment of applications through each environment — development, staging, and production. It removes the need for engineers to execute the same sequence of deployment commands for every release, making the process faster and less error-prone. Without reliable release automation, continuous deployment is not achievable at scale.

Release Orchestration

Release orchestration governs the logic of the entire pipeline: it enforces sequencing, triggers quality gates (such as security scans and approval workflows), and ensures that the right checks happen in the right order before code advances to the next stage. Think of orchestration as the control plane for the whole delivery lifecycle. Without it, individual automation steps work in isolation and the pipeline becomes fragile and hard to audit. Critically, orchestration logic should live in a dedicated tool rather than in a sprawling collection of ad-hoc shell scripts.

How to Get Started: A Practical Approach

If your team does not yet have a CI/CD pipeline, the most pragmatic approach is a phased rollout:

1. Establish CI and CD first. Get automated builds and tests running on every commit, and ensure every successful build is deployable. This foundation is required before continuous deployment can be added safely.
2. Plan a code-freeze window for setup. Coordinate with your architect and engineering manager to carve out time for pipeline implementation without disrupting active development work.
3. Measure baseline velocity before you make changes. Record how long it currently takes to go from a committed feature to a production deployment. You need this number to demonstrate the value of the changes you are about to make.
4. Add continuous deployment as stage two. Once CI/CD is stable and test coverage is sufficient, remove the manual deployment gate and let the pipeline promote builds automatically.
5. Track metrics continuously after launch. Lead time for changes, deployment frequency, mean time to recovery (MTTR), and change failure rate are the standard indicators of pipeline health. These tell you whether the pipeline is improving over time or degrading.

If your team already has a pipeline, the goal shifts from implementation to optimisation. Identify the slowest stages — commonly integration test suites and security scans — and work to parallelise or cache them. Every minute shaved off the pipeline is a minute closer to your users receiving value.

Measuring Success: The Metrics That Matter

You cannot improve what you do not measure. The following metrics give engineering leaders an objective view of pipeline performance:

• Deployment frequency — How often does the team successfully deploy to production? Higher frequency generally indicates a healthier, lower-risk pipeline.
• Lead time for changes — How long does it take for a committed code change to reach production? Shorter lead times mean faster feedback and faster customer value delivery.
• Change failure rate — What percentage of deployments cause a production incident or require a rollback? A rising failure rate signals inadequate test coverage or quality gates.
• Mean time to recovery (MTTR) — When a production incident does occur, how quickly does the team restore service? A mature pipeline with automated rollback capability significantly reduces MTTR.

Establishing baselines for these metrics before any pipeline changes go live gives you the evidence needed to justify the investment to stakeholders and to guide ongoing improvement efforts.

The Bottom Line

In a competitive software market, delivery speed and reliability are not just engineering concerns — they are business concerns. A well-implemented continuous deployment pipeline, built on solid CI and CD foundations, lets teams respond to customers faster, reduce the cost of defects, and attract the engineering talent needed to sustain that pace. The tooling and practices exist today; the question is how quickly your organisation chooses to adopt them.