IT-based innovation can come in many forms. Examples include advances to bolster customer or employee experience, to address new business models, or to augment the overall platform or ecosystem. Virtually all ladder up to an organization’s desire to digitally transform the business, and are considered to be a top priority for IT executives. In fact, organizations will spend about $2.1 trillion in 2019 on digital transformation technology, and related services1 and 94 percent of CIOs will spend up to 50 percent of their time on innovation.2 But beware, not all innovation is the same, and some may not be good for the enterprise if it's not conducted correctly. Here are some top tips on how to balance innovation and risk from those who have succeeded.
Start with a systems-thinking approach
In many organizations, the primary purchasing power has moved away from the IT department and to the business units as centralized IT budgets were cut over the years. This can lead to decisions where the objectives of a given project may be inadvertently narrow and misaligned with overall corporate plans. For instance, a manufacturing business unit may optimize for throughput, which may be at odds with legal and compliance processes. According to a Harvard Business Review report,3 one of the primary reasons why so many high-profile digital transformations fail is because they are “not hard-wired into business strategy and key processes.” A better approach to minimize the downstream risk of re-work is to develop a holistic and integrated picture early on, by ensuring alignment between IT and business unit heads and placing specific projects into context of the organization’s overall goals.
Implement a flexible DevOps strategy
While only one in ten organizations currently has no plans to implement DevOps4 due to the obvious benefits of delivering applications more rapidly, the path forward to this desired end state isn’t always clear. Integrating a single, unified DevOps framework that developers and testers can use alike is particularly difficult. This journey can be even more challenging if the realities of a heterogeneous organization aren’t recognized early on and develop a strategy that supports both non-agile and agile methodologies. Instead of a rigid platform, employ an integrated toolchain to deliver fully automated testing and continuous quality, as well as identify lifecycle management capabilities specifically developed to suit lean, agile and DevOps-focused teams that can operate at enterprise, team and individual levels. Soon enough, there will be releases several times a day without the concern of things breaking down when additional teams are pulled into the mix.
Modernize core business systems
In most organizations, there are a number of core systems that have been in place for many years, which generally have additional IP and processes built around them to add more value. For instance, CORBA software helps deliver more than 50 billion SMS transactions per day, and mainframe systems are often the systems of record and the repository of complex transactional and operational rules and policies that define the organization. Making dramatic adjustments to them and breaking tried-and-true practices can result in degrading ROI on existing investments, as well as risk that can manifest itself in the form of downtime, outages, security threats, and poor interactions with customers. While it may be tempting to start over with fresh-off-the-shelf technology as part of an innovation strategy, in many cases, a safer move is to build out from a known and established position. The strategy, often called IT modernization, allows organizations to extend current investments with software that bridges the old and the new.
Embrace advanced analytics broadly
While more than 50 percent of organizations are planning to leverage advanced analytics in the next 12 months,5 the scope of how it is planned for use is often somewhat narrow. The most common use cases are focused on driving the top line, such as boosting revenue with Big Data analytics of driving customer engagement with ChatBot technology. Innovation and the use of advanced analytics don't always have to focus on driving value; however, and in fact, both are equally applicable on managing the bottom line as well. With GDPR and other privacy regulations cropping up around the world, the need to safeguard citizen data is at an all-time high. Advanced analytics are critical in this endeavor, as they can help pinpoint the right information to protect. Security and risk professionals are also increasingly looking to advanced analytics to make sure they are investigating real threats versus chasing false alerts, plus identifying and taking action on insider threats such as abnormal logins user and entity behavioral analytics (UEBA) technology.
While it has been said that the only way to innovate is to take risks, the reality is not always that black and white. When public safety, global communications, privacy, and business viability are on the line, it often pays to strike a balance. With a long-term plan that is executed in a methodical manner with security and governance built in, IT executives can take calculated risks to grow and prosper without jeopardizing their organization or their end users.
1 - Excellence in the Digital Economy: A Blueprint for Success, IDC
2 - CIO Survey 2018-2019: CIOs Driving Distributed Innovation, CXO Unplugged, November 19, 2018
3 - Harvard Business Review, March 2018
4 - Forrester Research, 2018: The Year Of Enterprise DevOps
5 - IDG, State of Digital Business Transformation, 2018