Many companies are still grappling with the complexities of transitioning to a seamless Digital Business model. Organizations need to be able to drive this transformational change with speed, consistency, and at scale to ensure they stay ahead of their competition. Often, companies are averse to undertaking change, are worried about cost, disruption to the business, or having the right skills and tools to succeed. These concerns are not unfounded, reasons why Digital Business transformation fall short of expectations include:
- Lack of a single source of truth (SSOT)
- Absence of a business-led approach focused on outcomes
- Lack of a cloud-based Digital Business platform (DBP)
- Pursuing transformation with a big bang approach rather than an incremental one
- Failing to adopt an agile digital culture
A successful digital transformation is centered on a more agile and pragmatic approach that focuses on bite-sized outcomes that are essential to accelerating business growth. The solution is a unique approach of employing a DBP which enforces a Digital Business methodology (DBM) across the enterprise for consistency and scale. Companies can achieve meaningful results within eight-to-ten weeks in a highly cost-effective manner.
Digital Business Methodology
DBM is a holistic approach to business growth that is a more effective path than other alternatives. It is an outcome-driven, incremental approach that focuses on delivering results across the enterprise with speed, consistency, and scale. It is business led in collaboration with key stakeholders from ideation to deployment to optimize outcomes with a focus on simplification of end-to-end workflows through a SSOT.
Digital Business Methodology is a guided, adaptable ideation-to-deployment ecosystem that enables business owners, engineers, analysts, and scientists, and operational teams to collaborate seamlessly to achieve outcomes and drive innovative solutions. It is designed to enhance the current business operations without disrupting them, unlocking unlimited opportunities for growth.
Digital Business can be done on its own without disrupting the current business with an initial start in parallel to current ecosystem and can then scale up. The Digital Business methodology also establishes strict governance in terms of engineering rigor, quality, security, compliance (audibility, and traceability), and cloud services – ensuring that companies can operate with higher productivity and predictability.
Digital Business Platform
Enterprises face multiple challenges when creating a cloud-based DBP within their existing technology environment. These challenges include:
- Optimizing cloud adoption
- Delivering a cloud self-service capability
- Building at scale
- Creating an end-to-end DevSecOps environment
- Leveraging new cloud technologies effectively
- Tracking costs in real time
- Failing to utilize a SSOT
- Taking an end-to-end data/product engineering approach
- Having core and domain architecture
- Providing centralized reusable assets
- Creating and consumption of self-service functions
A cloud-native application development platform offers a simplified end-to-end collaborative environment that is independent from the existing complex, siloed environments. It empowers users through self-service with automated governance via policy blueprints integrated into the engineering ecosystem. It reinforces an agile culture with intelligent DevOps pipelines and eliminates the complexity of discrete technology environments by harmonizing business functions across the enterprise into a SSOT.
The DBP establishes and applies end-to-end industry best practices in relation to security, compliance (audibility and traceability), quality, reliability, and observability. It creates a service catalog providing reusable playbooks, components, and assets with governance for higher productivity.
The DBP enables a continuous learning culture with real-time productivity and predictability dashboards to measure organizational and team level-maturity. It also allows implementation of the DBM across the enterprise with end-to-end visibility, consistency, and scale. Cost is optimized with access to detailed metrics, monitoring, and FinOps.
Implementing a DBM Within the Current Technology Environment In Three-to-Twelve Months
Typically, companies take a piecemeal approach to Digital Business enablement by leveraging simplification and self-service. A holistic strategy encompasses an overall assessment of the current architecture, tools, and techniques, understanding the value of cloud adoption; and focusing on data and product engineering.
The DBM addresses challenges companies face with a focus on cloud strategy adoption, technology fluency, toolchain and cloud service optimization, governance, overall architecture, proactive cost analysis and controls, and self-service for scale. It establishes an end-to-end software delivery lifecycle, fully automated infrastructure provisioning, access management, data ingestion pipeline, DevSecOps, orchestration and self-provisioning of all functions.
This happens in a collaborative environment with governance through rationalization of both existing tools and new data technologies like Snowflake.
The hybrid data mesh architecture for enhanced data, discovery, accessibility, speed, performance, and standard prices. Another benefit is a self-tracking, central and separate core data engineering, and domain-based self-service environment for analysts and scientists.
Operational inefficiencies are identified and eliminated with the adoption of end-to-end system observability, the automation of runbooks, and self-healing systems.
New technology like Snowflake allows separation of the consumption layer for businesses and AI/ML in the domain area. This also segregates the costs, and this traceability helps drive operation rigor. For domain companies can leverage AWS/Azure cloud.
Working closely with a company’s engineering teams, analysts, and scientists typically operate within two use cases. The first focuses on delivering business outcomes with speed and consistency in partnership with a customer’s business through an agile and DevOps lens, and creation of a SSOT. The second utilizes smart machine learning analytics and appropriate algorithms to create better predictive tools and forecasting. This involves joint investment to deliver results in eight-to-ten weeks.
Parallel to this, capability centers, expertise in cloud, DevSecOps, engineering teams across data/product, cloud, and site reliability converge with an end-to-end perspective to conduct assessments, provide recommendations, and provide a pathway for overall architecture, governance, automation, and self-service. This approach is adaptable within the current environment based on the company’s size and maturity. This can deliver outcomes within two- to-ten weeks with a joint investment.
The unique combination of a DBM and DBP enables enterprise level adoption, collaborative culture, and scale through agile engineering. The solution includes engaging business teams, taking an agile approach, and adopting a DBM enforced by a DBP in the cloud. This combination is a powerful formula to create sustainable change, outcomes, and growth in three-to-twelve months depending on a company’s digital maturity and technology complexity.
Altimetrik has successfully taken this approach with many of our clients to be more effective in data and product engineering for unlimited growth.
