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Conclusion: The availability of modern, Cloud-based, omnichannel-focused stakeholder and customer relationship management (CRM) solutions is disrupting expectations of how public sector organisations should interact with their stakeholders, be it citizens and constituents, the business community, research or other agencies.

It is not just that new CRM solutions have additional features and modules when compared to more traditional CRM solution with histories that predate social media. Rather, the emerging modern CRM paradigm is focused on automation and mass personalisation of stakeholder communication rather than sales management.

A public sector’s CRM modernisation effort must, therefore, be based upon a firm understanding of the organisation’s most valuable stakeholder experiences. One way to achieve this understanding is to develop a stakeholder experience strategy.

Note: A sister note on this topic for private sector organisations is available.

Related Articles:

"CRM modernisation Part 1: Strategy, planning & selection" IBRS, 2018-09-04 05:20:15

"CRM modernisation Part 2B: Creating a customer experience strategy" IBRS, 2018-09-04 06:47:58

"CRM modernisation Part 3: Roles & responsibilities" IBRS, 2018-10-04 13:09:21

"Design thinking – do not rush the empathy" IBRS, 2016-05-05 03:03:00

"User Centred Design or Design Thinking" IBRS, 2017-07-03 23:24:11

Conclusion: The potential, and corresponding increased expectations of, modern CRM is causing many organisations to re-evaluate their existing CRM solution (or multiple solutions) with a CRM migration.

The decision to migrate to a new CRM solution should not be taken lightly. Given that the management of contacts (e. g. customers, stakeholders, citizens, etc.) is central to every organisation, changing how an organisation communicates with and serves these contacts must be viewed as a strategic initiative.

Therefore, it is vital that each organisation create a strategy, and subsequent plan, for its modern CRM journey. In this paper, IBRS outlines the typical journey for an organisation creating a strategy, planning for, and finally selecting a next-generation CRM solution.

Related Articles:

"CRM modernisation Part 2A: Creating a public sector stakeholder experience strategy" IBRS, 2018-09-04 06:46:34

"CRM modernisation Part 2B: Creating a customer experience strategy" IBRS, 2018-09-04 06:47:58

"CRM modernisation Part 3: Roles & responsibilities" IBRS, 2018-10-04 13:09:21

"DIY or ready-made? Choose your AI adoption path carefully" IBRS, 2018-07-05 03:00:08

"User Centred Design or Design Thinking" IBRS, 2017-07-03 23:24:11

Conclusion: Organisations seeking to ride the new wave of AI-enabled transformation are facing a clear choice when it comes to the adoption of supporting AI capabilities such as machine learning or speech recognition, either:

  1. DIY (Do It Yourself) – By adopting AI early as stand-alone services; or
  2. MODIFY (Make Others Do It For You) – By waiting for AI functionality to be embedded in existing solutions.

Deciding which path to take requires that organisations reflect on their current maturity when it comes to building solutions. Only those organisations that can honestly demonstrate full development lifecycle capabilities and that have contemporary development tools and frameworks should expect anything but proof of concept success with DIY approaches to AI solutions.

Related Articles:

"Machine learning will displace “extract, transform and load” in business intelligence and data integration" IBRS, 2018-02-01 10:03:37

"Preparing for the shift from digital to AI-enabled transformation" IBRS, 2018-06-01 04:10:21

"Proactive optical character recognition of incoming content will accelerate AI-enabled automation" IBRS, 2018-03-06 06:54:57

Conclusion: During January to March 2018, IBRS conducted a detailed market scan of eForms vendors and their products in the Australian market. The market scan was structured around common selection criteria and comparisons developed. The following snapshot summarises the results of the study, and may be used to assist with the development of eForm and workflow solution shortlists.

This snapshot includes eForms solutions that are in use within Australian organisations

Related Articles:

"How to succeed with eforms Part 1: Understand the need" IBRS, 2018-01-03 05:42:10

"How to succeed with eforms Part 2: The five most common eforms challenges" IBRS, 2018-02-01 10:06:14

Conclusion: The enterprise application marketplace has seen some changes in the past two years, with new entries, consolidation and acquisition, particularly in the mid-market of ERP finance systems. IBRS recently investigated a cross-section of ERP finance systems from top tier to the smaller players including, but not limited to: SAP, Oracle, Workday (Finance), Technology One Microsoft Dynamics 365 for Operations (Microsoft Dynamics AX), Sage X3, NetSuite, Microsoft Navision, Sage 300, Great Plains, MYOB, Xero and SaaSu.

This research paper includes a comparison of current functionality available across three popular mid to upper market ERP finance systems, namely Sage X3, Microsoft Dynamics 365 for Finance and Operations (previously A) and Oracle’s revamped NetSuite. They have been reviewed given their strength in the finance and operations functionality.

Conclusion: Due to years of tactical software deployments in response to urgent digital transformation uplifts, organisations have created a jungle of business intelligence (BI) technologies deployed in the absence of a well described and comprehensive approach to the challenges faced; challenges that will continue to increase with the shift to AI-enabled transformation.

Instead the majority of solution paradigms have centred around the application of emerging technologies with little articulation of a coherent architecture traceable to the underlying functional or non-functional requirements required to support a well governed and long lived data analytics platform. Instead, with each new trend in reporting and analytics, e. g. big data, results in a litany of partial solutions.

Enter Data Vault 2.0 (DV2.0) is the first well described architecture, methodology and modelling approach to emerge from the BI community in the last 5 years. DV2.0 provides a solid basis for organisations wishing to avoid the data sins of the past and adoption should be a top consideration for the inevitable expansion of BI that flows from business application transformation and as part of a clear DataOps strategy.

Conclusion: The development of AI-based solutions is heavily dependent on various types of data input in the form of either:

  • Large data sets used to conduct experiments to develop models and algorithms for predictive analytics, optimisation and decision recommendations; or
  • Enriched and tagged corpuses of images, audio, video and unstructured text used to train neural networks using deep learning techniques.

While at first the data management needs of AI-based solution development might leverage both data scientists and their existing business intelligence platforms to exploit these types of data, the actual lifecycle management needs of AI developers will expand quickly beyond the boundary of the traditional enterprise data warehouse.

Therefore, like the source code and configuration data underpinning transactional business applications, the raw data and algorithms of AI solutions must be managed by evolving DevOps practices towards a comprehensive “DataOps” model.

Conclusion: Although online digital platforms are in ready supply, organisations remain unable to avoid the receipt of critical information in the form of paper documents or scanned images. Whether from government, suppliers or clients, organisations are faced with written correspondence, typed material, completed forms or signed documents that must be consumed. For a variety of reasons, it may be unreasonable or impractical to expect this information to be sent in machine-readable form.

However, machine-readable content from incoming information, both past and future, is emerging as a prerequisite to exploit artificial intelligence and machine learning as part of digital transformation. Therefore, organisations need to re-examine their data ingestion strategies and move proactively to the use of optical character recognition on incoming paper- and scanned image-based information.

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Conclusion: IBRS has observed that many organisations’ eforms initiatives face five common challenges. To help ensure the best long-term outcomes for an eforms initiative, each of the five challenges must be considered, and remediation strategies put in place.

Related Articles:

"How to succeed with eforms Part 1: Understand the need" IBRS, 2018-01-03 05:42:10

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