Voices from Accenture Public Service

Government organizations are facing a technological crisis. Core Legacy systems are inflexible and unable to keep up with rising demands. And citizens are increasingly expecting a similar level of experience and service from government organizations to what they receive from commercial ones. It’s time to meet the challenge of disruption and changing expectations head-on and re-invent the core.   

Legacy systems modernization for improved customer experience in government

Changing core technology is hard. Technically, it’s challenging to pull apart systems that have grown in complexity over many years. There are significant challenges in reinventing organizations that are invested in maintaining the status quo. During the past five years or so, much of the work focused on digital user interfaces for existing core systems. However, sustaining the current core could become a potential technological nightmare. Updating the core is now critical as the constraints imposed by existing systems are holding organizations back from creating new opportunities. Technical debt is real and needs focus and attention from Public Service Technology Leaders. 

By 2020, enterprises that continue to invest in heavily customized, traditional, monolithic ERP solutions will be 75% less effective in supporting digital business strategies – Gartner, Government CIOs Should Consider Postmodern ERP to Modernize Legacy Business Applications  

Disruption is inevitable at this point and can quickly undermine business operations. Organizations that hold back and approach system modernization with a “keep the lights on” philosophy lose their appeal to customers and citizens. We all have seen this happen in the travel, tax, accommodation and banking industries, and governments are by no means immune. Governments compete on a global, regional and local playing field for talent, investment, and industry. Those able to respond to change will be more attractive, and therefore, successful.  

While modernizing core technology is hard, it’s not impossible. The scale, risk, and complexity of change needs care and commitment over multiple years. Organizations must focus on becoming agile—able to change both their systems and their organization’s structures and processes to adapt to future challenges. They also require a strong vision, informed by technology innovation, industry insights and leading practices, that embraces openness, collaboration, and flexibility.  

While it may appear attractive to chase short-term solutions or alternatively embark on multi-year core transformation programs, both can be unappealing or even disastrous. Long-term visionary thinking with the belief that agility will lead to growth opportunities and evolve the organization amid disruption will future-proof it. In my next blog, I’ll share our new approach, Continuous Transformation, which can help government organizations find a middle ground between a keep the lights on (do-nothing) strategy and complete systems replacement. In the meantime, please follow me on Twitter and LinkedIn. 

Further Reading: 

The Future of Back Office Government Operations: Transforming to Improve Citizen Services 

Modernization in the Digital Era: IT at an Inflection Point 

Government in an Era of Digital Disruption 

Response:

  1. @Carl Ward – your observations regarding effective modernisation being dependent on agility are spot on, as is the need for incremental or evolutionary development in your Continuous Transformation model. Aside from the critical success factors of governance and change management, too many major transformation initiatives forget about the complexities of the core data platform, and a. the increasing need to integrate multiple sources of data, in real time (viz key recommendation of Patrick McClure’s report on his 2017 Review of the Welfare System) from disparate sources) from not only other federal and State/Territory government agencies but also potentially from employers and b. to accommodate the inevitable policy and legislative changes which need to be addressed even as a technology solution is being developed. We too often read in the IT press of major projects which have taken far longer than anticipated, or failed at great cost, due to unforseen complexities and massive data migration problems which are typical in the health and human services domains. This is often (but not always) as a result of trying to use 30+ year old relational database technologies to manage complex, changing data and business rules at scale.

    The good news is that it does not have to be that hard. What many global brand name commercial as well as some forward-thinking (and in some cases desperate) government organisations have discovered is that an operational data hub architecture pattern provides the flexibility to support both transactional and analytical workloads simultaneously (thereby doing away with the need to duplicate operational data in data warehouses or data lakes), and the agility to ingest massive amounts of disparate data, in real time, from legacy systems without the up front overhead of data modelling and mapping prior to loading. Provided the technology platform has the ability to deal with disparate data types, in real time, has the flexibility to add and amend metadata at will, bombproof security and audit, and provide for flexible deployment and all the usual enterprise HA/DR infrastructure requirements, there is a very high probability of success in a much reduced timeframe. There are plenty of good examples of genuinely innovative transformation, if only public servants and their technology advisers were to look for them. The massive Healthcare.gov system in the US is a great example, in which the system build commenced before the legislation had been finalised, secure in the knowledge that the data platform was agile enough to accommodate changing needs even before requirements had been locked down. Suffice to say Medicare and Medicaid Services met their legislated deadline in 2013 in spite of having to accomodate both enrolment data from multiple federal agencies, as well as healthcare insurance plan data from multiple private sector providers.

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