How Do Chief Digital Officers Promote Transformation?

This is a guest post by Jason English (@bluefug), Principal Analyst, Intellyx

In business, waiting for change is no longer in style.

Today’s enterprise has an endless fascination with achieving innovative new capabilities that will provide a competitive advantage — as well as a short attention span when it comes to the organizational and technical limitations holding it back.

The urgent need for significant technology-enabled change within enterprises has created an executive opening over the last decade for the emerging Chief Digital Officer (or CDO) role.

Whereas the CIO focuses on managing internal systems, a COO might focus on organizational efficiency and sales, and a CTO could work toward productizing technology, the CDO’s leadership should include an avid devotion toward customer-centric improvements, strategically enabled by technology.

A recent research brief said that 82% of enterprise leaders believe their CDO has helped them achieve their digital transformation (DX) and customer-centric business goals.

That’s an insanely successful track record, given two-thirds of enterprise IT projects are still running over time and budget goals, and fewer than 30% of projects are considered successful by some reports.

What’s the CDO’s secret to successful digital transformation?

The Challenge of Uncoupling Dependencies

Attend any IT industry conference over the last decades (remember those?) and you would hear transformational keynotes from digital visionaries, whose teams designed or declared their company’s application stack from scratch, using the best technology available at the time.

Data architectures evolved from procedural records on mainframes, to relational Oracle and SQL databases and big iron enterprise systems, to data warehouse and lakes — in SQL and NoSQL varieties, which could live on-premises or in cloud infrastructure.

Integration evolved too, from early EDLs and message queues, giving way to event and service buses, then web services, then service-oriented architecture, then REST-style approaches, culminating in today’s API-driven microservices and cloud-native approaches.

Every evolution of integration architecture represented a leap forward in agility, interoperability, scalability, and some abstraction or decoupling of logic and data. Despite so much progress, all of these approaches fundamentally involve the act of fielding a request and moving bits from one place to another in order for an application to get some unit of work done.

No matter how modern or loosely coupled the integration mechanism seems to be, requests and responses are bound to create dependencies between upstream systems of record and applications, as well as between applications and the downstream services — and customers — that consume them.

In addition, since a full rip-and-replace of the core systems that run the business is usually too risky, each messaging tier and point-to-point integration becomes a new dependency for existing applications and systems of record that needs to be monitored, optimized and tested — all the while generating heavy compute, data and storage costs.

It’s challenging to launch new applications and services atop conventional system architectures, when the business can’t afford to let the flow of data get out of synch — even for minutes in many cases.

DIY vs. DIH: Defying Traditional Integration Limits

How can a CDO effectively escape this gravity field of traditional systems and integrations to rapidly launch new apps and services, without being brought back down by mounting technical debt?

You know that early scene in Raiders of the Lost Ark, where Indiana Jones is in an ancient tomb, trying to swap a bag of sand for the relic he is about to steal — as if the sudden change in weight wouldn’t set off a deadly boulder trap?

Fortunately there is a ‘trick of gravity’ that can be employed to make this architectural swap work without setting off any costly traps.

A digital integration hub (or DIH) offers a modern integration fabric architecture that overlays existing systems and data sources, consuming them into a single high-performance data store that application developers can build new apps and services atop by querying the DIH through common API interfaces.

What’s interesting about this approach is that if you were to look up from the bottom of the stack of data warehouses and enterprise systems, it would seem that nothing requiring a change management crisis has really happened.

As developers build new web clients and SaaS apps, the DIH no longer queries the system of record. Instead, event-driven integration notifies the DIH if a record changes and pushes that change. Once enough pathways have been consumed, the new apps simply interface with the DIH for a lightweight, low latency abstracted version of those once intractable batch-running backends.

Avanza Bank, a leading international financial services firm, was able to consume and replace its legacy SQL database with a high performance in-memory data platform that is powering their digital services, by putting the GigaSpaces DIH between its small, agile development teams and the complexity of their data models.

Within the first year, a small team was able to leverage the DIH and its associated SmartDIH in-memory data store to scale its operations while reducing latency and cloud cost overhead. The firm has continued to deliver hundreds of new customer-facing applications to become the fastest-growing trading platform in its region, reaching more than 5X customer growth over the last 8 years.

The Intellyx Take

CDOs and executives seeking digital transformation have always been challenged by the dual-edge sword of integration, which offers two unpalatable options.

Either commit to integrating new features with legacy back ends carefully and slowly — or have teams deliver new services faster, while accepting the disconnect and mounting technical debt that approach will later surface.

Not anymore. A digital integration hub can allow new services and apps to get traction quickly and support customer and analytics needs with fast, current core system data — without the later technical debt heartburn and implementation risk of point-to-point integration.