A positive customer experience remains the Holy Grail in today's digital age, with businesses striving for a seamless, unified journey. However, businesses continue to rely on disparate systems and the data generated, which results in silos and a fragmented client journey.
The concept of a unified 360-degree view of the customer and their experience remains elusive, especially in the face of the proliferation of cloud systems and the internet of things, plus client applications generating new data streams.
However, all is not lost. Thanks to a new generation of cloud technologies, analytics, process automation and open API platforms, there is hope on the horizon.
These advances are paving the way for the creation of more integrated workflows infused with data, breaking down organisational silos. Let's unpack these developments.
Visual workflows and context-aware data
This refers to a practical integration of visual workflows seamlessly complemented by context-aware data − a collaboration that not only enhances insights but also forms a solid foundation for well-informed decision-making.
This is augmented by the incorporation of writeback capabilities, plus facilities collaboration that enable real-time updates which improve data quality.
Positive contributions aimed at improving customer service are made at every stage of the process flow.
Add to all this the ability to ingest unstructured data, such as scanned documents, and new avenues for analysis are unlocked. Positive contributions aimed at improving customer service are made at every stage of the process flow.
Furthermore, this leads to refined decision-making, prescriptive insights and feedback loops, enriching the overall operational ecosystem.
Transformation building blocks
These foundational elements are readily available within various technological components. While such possibilities have always existed, the challenges of constructing and maintaining these systems were significant.
However, recent advances in open API integrations have streamlined this process, making it more possible than ever to establish and sustain transformative systems.
Business use cases and benefits
Recent technological advances have brought together diverse tools, including analytics, data capture, process analysis and file analysis of unstructured data, into a simplified single stack.
- Intelligent writebacks (data entry/data capture) enabling writeback from the point of interaction with systems and data. The key is the two-way flow between two systems infusing insight into the moment of action/or decision, and the businessperson being able to capture information back into the system for improved collaboration or intelligence. This incrementally builds context-aware information, or ultimately kicks off the improved data-driven decision.
- Process analysis: It's now possible to visualise processes, understand data flow, pinpoint bottlenecks and then quickly identify where improvements are required. Drilling into processes through hierarchies that group information all the way through to product level visibility is enabled. Furthermore, a visual guide can be built, one that shows users exactly where they are in the case management and approval processes developed with the writeback capability.
- Accessing and analysing unstructured data: This is reading, profiling, organising and analysing unstructured or semi-structured data. Imagine systems reading document repositories and bringing back relevant information in context. This includes Word documents, JPEGs, e-mails, agent conversation logs, etc. This opens up a new frontier of insights, multiplying the value of analytics investments, transforming them into an actionable and collaborative platform for a wide range of use cases.
Let's explore some practical use cases and associated benefits, exemplifying how these capabilities converge in common scenarios.
These building blocks can be stacked to improve a myriad of existing business cases, including budgeting, planning and forecasting. There is a shift away from traditional spreadsheet-based processes that cover the foregoing but also include data quality improvements, simulations, collaborations and more.
Combined with actions, automations and machine learning technology, analytics platforms can be used to quickly transform and modernise manual and repetitive processes, including sales planning, to the full range of financial functions already described and also includes flow analysis.
Today it is possible to enter contextual information directly onto dashboards and thereby reveal why any specific number has altered (up or down).
Moreover, sales forecast tools can predict the volume and value of potential sales in a coming quarter. Instead of using spreadsheets, information can be entered directly onto a sales dashboard, which then displays what was achieved in the current quarter versus the same quarter last year.
It is also possible to provide an AI-based sales forecast for the quarter based on a well-trained predictive model.
Depending on users' knowledge and the information at their fingertips, it is then possible to enter sales forecast data and save it directly on the business intelligence (BI) dashboard.
Sales staff can enter forecasts on time and all data is captured in one place with no copying or moving of data across spreadsheets. They can also use the same BI dashboards and see their own view of the data entered and if necessary, adjust numbers or add narrative for context.
Visuals can depict a holistic picture of the forecasting exercise and highlight potential bottlenecks or delays. Once the quarterly forecast exercise is finalised, reports can be generated for the company executive team to scrutinise and evaluate.
Expanded capabilities
There is a shift from exporting to spreadsheets or using them to augment analytics data and applications. Users are allowed to collaborate on data-driven tasks; for example, capturing the progress and status of projects and programmes.
Creating planning systems that allow users to combine their knowledge and intuition with AI models leads to better predictions of future demand.
Secure and ready for data-heavy environments
Security is paramount in this transformative journey and must be viewed as a key component in this evolution. These technologies are designed to maintain large amounts of data securely within an organisation's network, including automated multi-node installations, facilitating scalability.
User permissions provide granular control over user and group-level authorisations and data security, so all data remains within the company's network, meeting the highest standards of security.
As we embrace this convergence of workflow visualisation, data insights and task automation, the future looks promising. It's a path that leads to more efficient processes, enhanced customer experiences and the unleashing of untapped potential within data.
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