Decision-as-a-Service: Applying Analytics at the point of Capture (Part 2 of 2)

In my previous article, I introduced the concept of an Automated Decision Management (ADM) platform evolving from the likes of ECM and BPM as we look towards the future. Products within 3 distinct categories (capture, content management and output management) will join forces to create a new software and service category, augmented and enabled by super advanced semantic technologies.

The question is how far is this concept from reality?

Automated Decision Management: Barriers to Adoption

Many digital systems and technologies are impacted in realising an automated decision platform. The following key challenges need to be solved if this vision is to become reality.

• The integration of structured and unstructured data systems, or preferably a content platform to handle both. The worlds of ERP and CRM need to merge with the likes of ECM and BPM
• The integration of internal data systems with external data sources, particularly Social Media to monitor, understand and react to live consumer sentiment
• The development of a new form of middleware hosting a number of adjacent technologies
• The advancement of super-intelligent linguistics – technologies which understand human language and intent
• The evolution of classic rules engines to dynamic decision engines capable of understanding and reacting to unpredictable events via adaptive business logic
• The integration of outbound communications, including marketing automation and content composition platforms to inbound and process management platforms, such as capture and BPM

Conclusions & Outlook

• Enterprise Content Management platforms will evolve from managing content, to managing processes, to managing decisions – streamlining interactions, shortening response times and identifying threats and opportunities faster than ever
• A new form of intelligent system will begin to emerge – Automated Decision Management platforms will merge capabilities across a multitude of content-driven technologies to handle end-to-end human tasks
• Intelligent systems will adapt to events on-the-fly – decisions will be made in real-time based on a combination of historical behavioural data and contextual data “in-motion”
• Intelligent systems will also boast human-like senses, gaining the likes of machine vision and thus being able to “see the world for themselves” – opening up a whole new space for intelligent monitoring and surveillance systems – tracking consumer behaviour, deploying counter-terrorism, automating traffic management etc 
• The Internet will continue to grow its knowledge base with businesses and consumers alike increasingly able to tap into this knowledge pool on-demand – offered as “services” via a subscription model

Organisations looking to get ahead of the game need to start thinking and planning ahead in order to gain long-term competitive advantage.

The following recommendations are made:

• Understand the vision of the future, but don’t rush to get there overnight – systems need not be fully automated from day one
• Develop the architecture to allow for expansion – be pragmatic, start small and look to add more advanced capabilities over time
• Recognise the business case is not primarily about productivity, or cost cutting, but in driving superior customer experience, which directly drives increased revenue
• Focus on optimising select business processes, each process justifying its own mini business case
• Understand that a technology platform is not the single answer to antiquated business processes in need of a revamp, it is only part of the solution
• Work with third-party experts to re-engineer business processes and transform operating models prior to technology selection and deployment    

Decision-as-a-Service: Applying Analytics at the point of Capture (part 1 of 2)

Many organisations have recognised the need to apply some kind of document and data capture technology on the journey to the digital enterprise. After all, you cannot realise the vision of the paperless office if you are still pushing paper around.

Leading organisations are now embarking on the next phase of their digital journey. For those that have laid the initial foundations, the transition to the digital enterprise is less about paper and more about data.

“Now that we are capturing and routing all inbound documents electronically – how do we make use of the actual content?”

From Digital Mailroom, to Customer Dialogue Management

The description of capturing and routing all inbound documents is of course the digital mailroom concept. Such systems point to proven ROI – speeding downstream business processes through automated classification and routing, thereby increasing the overall effectiveness of an organisation. Things get done quicker and smarter, with less effort, less paper and less cost. But what comes next?  

Looking at the bigger picture, all processes, communications, interactions and decisions, be that in a consumer or business capacity, have one thing in common – they share 3 core components – an input element, a processing element and an output element.  

• Input – the data flowing into the central system from outside
• Process – the action of manipulating the data into a more useful form
• Output – presenting the data as information in a user-friendly way

In other words, the information flow moves from data, to insight, to action. 

In this sense, the Digital Mailroom, acting as the input element, represents only the start of the value chain and therefore just the beginning of any end-to-end business improvement initiative. Traditionally, the processing element “what is the value of this content, and therefore what do I have to do with it?”, or more simply, the decision point – has been a job for humans, but will increasingly become a job for machines as more advanced technologies emerge.

Organisations across the globe have realised the benefit of handling incoming content (paper, email, web, PDF) through one multi-channel content capture platform – standardising the capture process. But what about the response process?

Leading organisations are one step ahead and have recognised the strategic importance of the Digital Mailroom and its ability to drive customer-centric activities. The system is set to evolve from a purely admin-centric operation, stationed on the organisation periphery, to one placed at the heart of business operations driving high-value, high-impact customer dialogue.

Decision-as-a-Service: Automated Decision Management  

The concept of a fully automated input-process-output chain of events – touchless processing with minimal, or zero human interaction, is human-computer interaction (HCI) at its best and straight out of science fiction. Ask a question, receive an answer – in real-time. Sure, it is a futuristic one, but an increasingly realistic one when you begin to combine advanced technologies in recognition, analytics and linguistics.

Imagine a state-of-the-art system where incoming content (requests, enquiries, complaints, questions) is analysed with human-like interpretation to drive automated interactions, decisions and actions (answers, offers, recommendations, approvals) in near real-time or even real-time itself.   

Such a concept gets close to a real-time conversation platform between businesses, suppliers, customers, employees and artificial agents, with a myriad of one-to-one interactions in a futuristic, always-on, hyper-connected society. No waiting, no down-time.

Setting the Scene

As a customer of a large mobile phone provider, you would like to email customer services with a specific complaint – you are receiving spam text messages and you are requesting they put a stop to it within 2 days, otherwise you will switch provider.

In today’s environment, not only is this not possible due to a lack of multi-channel capabilities by the provider (they cannot handle email), it is also reliant on a human processor who has to understand the nature of your request (requires human logic), and who has a number of other tasks to handle (delayed response). Further, due to a lack of integration with your historical customer data the agent is unable to appease you when it matters most (loyalty programmes and special offers) and the net result is that you remain an unhappy customer (defecting to the competition).  

The business case stacks up when you multiply the issue across your customer base. Not only does the mobile phone provider have a potential customer attrition problem, it is also missing out on leveraging customer insight, in real-time, for up-sell / cross-sell opportunities. Reason enough to put forward a case for customer experience optimisation and the subsequent implementation of more advanced technological capabilities. The outcome: happier customers, healthier balance sheet.

Integrating Multi-Channel Input with Multi-Channel Output…and a whole lot in between

The idea of an automated business decision platform – driven by an integrated input-process-output chain of events sounds simple in practice, but in reality is rather complex. The truth is that there are a number of enterprise software applications implicated in this story, not least CRM, ERP and Database Management systems holding a plethora of historical data, which may, or may or may not need to be drawn upon at the “decision-point” in real-time.

In addition, the output element – or outbound communications component – is fragmented between the fast-growing marketing automation space and declining print media space. Traditional document composition systems will need to mature into multi-channel output systems (including mobile and voice capabilities) capable of creating meaningful content on-demand, as opposed to heavy-duty document production.

And last but not least, the glue that joins it all together, semantic analytics, acting as the central brain and decision-engine, remains a super-technology in early adoption. Even then we should not discredit human intervention – after all, we are still some way off true artificial intelligence, meaning intelligent systems will still require a form of human touch. It is likely that decision management platforms will initially surface as decision-support engines, running as a centralised enterprise service. Consequently, they will automate much of the business process, but still require human guidance.

Part 2 of this article will explore barriers to adoption, and key recommendations to move this concept towards reality.