Among those that report projects failing 50 percent indicates a high volatility with over 20 percent of all projects failing.
There are three strategic ways to tackle the “legacy system” problem:
The legacy system is gradually restructured. When a new change is to be made, a timeframe is planned to refactor the affected parts of the system to ensure that the changes will not harm the existing processes.
A completely new system is being developed from the ground up with a plan to eventually migrate all existing users of the legacy system to the new one.
The active development of new features ceases and the legacy system is switched to a “maintenance only” mode, when only critical bug fixes are released.
There is no single solution that fits all and a particular approach can be applied depending on existing business needs. Although “rewriting” the system may seem easier than refactoring there are strong arguments against it. It is a risky endeavor with a long and not-well-predictable timeframe to complete. Generally Radar believe that the “refactoring” approach should be the first option to consider and to work the restructuring gradually in smaller pieces.
The re-design or work around challenge
Given the present transformation pressure and pace in technology change all organizations must be able to re-design or re-engineer processes. Today this comes at high risk and cost. Although traditional Business Process Reengineering (BPR) is a necessity it comes with many pitfalls. One is the risk associated with reengineering to many steps. Another is the lack of competence to perform the task and time wasted in the process besides the more obvious high cost and high risk as in most IT projects.
In all too many companies, reengineering has been not only a great success but also a great failure. To succeed you need to focus on both breadth and depth of the project. You must first identify the activities to include in the process being redesigned that are critical for value creation in the overall business unit. A process can be as narrowly defined as a single activity in a single function or as broadly defined as the entire business system for the business unit – Breadth.
The successful redesign of a broad process requires the complete restructuring of the key drivers of behavior so that actual results measure up to the redesign plan on paper -Depth. Even with sufficient breadth and depth, a reengineering project will fail without the full commitment of senior executives.
Re-design will be a real challenge unless you can create smaller bits – workflows – to focus on and build step by step.
The innovation challenge
The discussion on how technology is transforming business often focuses on the size of the data stock – to the exclusion of how we might interact with it to further larger business aims.
Harnessing these data flows requires new tools, techniques, and business models – elements arising in several economic sectors. One of the most recent is the Internet of Things (IoT), a connected network of physical devices, sensors, and software that enable physical objects to collect and exchange data. This network is already generating large, complex real-time data flows – and serving as the basis for a generation of businesses dedicated to creating and capturing value in new ways.
But the value of flows, and their impact, transcends IoT. Ultimately, the value of data in such a format lies in analyzing flows in order to detect, and act on, emerging patterns in real time. Whoever can build models and workflows that leverages data flows most effectively and creatively will have the opportunity to create a lot of value. The richer the flows – and the more diverse the analytics brought to bear on them – the more companies can learn, and the larger and more fundamental the changes and opportunities that will result.
Innovation is not only about creating new things. Much of today’s innovation comes from integrating new technology or data, relations or transactions in different industry specific flows. Most organizations would therefore benefit from using a data centric workflow engine to test, adjust and launch flows from.