Being in the IT Industry for more than 25 years, I thought the digitization of business processes is something we did since the 1970ies. Which is true, in IT we digitized business processes along the technological capabilities and performance we had at the time. So, what is different today when we talk about digitization?
Our ability to mobilize applications, use modern interfaces with a better user experience (UX) which makes it intuitive to interact with a device, having Artificial Intelligence (AI) that allows speaking to the device and getting advice by a service is unparalleled today. Our technical capabilities changed so dramatically that we can create completely different experiences to make digitization happen.
Second technology is now available to almost everyone, anytime, anywhere. And you don´t even need a terminal to access information in an office. There are relatively cheap and affordable large scale services that can be accessed on the go. That’s the difference and offers tremendous opportunities. So digitization is a leap step ahead the past, it is fast, affordable and easy to use.
Digitization had two starting points
The ability to electronically compute results and have transactional systems was the first starting point and the ability to have analog contents available at a computer screen the second one. Content Management (CM) has evolved over time by transferring analogue content such as invoices, contracts and documents to an archive system and making them available for search and retrieval. That was the starting point of Enterprise Content Management (ECM). Adding the ability to collaborate made it Document Management. A company could digitize content and gave access during to the archive to retrieve and use information for business. This has mainly driven efficiency. Still, 40% of companies have not fully digitized the content to fuel business processes today.
Content management has evolved from this rather static approach in files and folders to Process Content Management (PCM) or Contextual Content Management (CCM), where the user gets the right content at the right time, such as an invoice with delivery note and the order for a particular transaction, comparable to Amazon© and others offering further products to buy while shopping a specific product.The most important value driver is productivity in enterprise environments and modern applications that are already in use today. The availability of more data points and even IoT (such as machinery data for installation documentations in field service) helps improve contextual content management every day. That’s the business we’re in and deploy solutions for customers.
We believe there is a convergence of trends for the content industry. The trend to mobilize applications and mobile services will connect with the enterprise world of content management. Why is that?
Mobilization and Consumerization of business services is mainly driven by the end customer to gain access to services such as ebanking, booking, shopping or any other service. This also reaches to the employees and business partners who want to access applications with an easy-to-use interface at any time. The digital workplace is an imperative in the war for talent, ask your Millennium workforce. Though the corporate world is different as the services are related to sensitive confidential data, the backend systems are not easy to change and regularly provide only a limited mobile and user experience. Most customers have to deal with multiple environments and cannot lock in everything on one system or platform. But the demand for such solutions and new business models is pressing.
In the past, companies have asked an agency to create an application, such as a portal for a single use case, and IT struggled to gain access to every back-end system to make it an integrated, robust business process. Meanwhile, another department of the same company contracted another agency to develop other processes. That was neither ready for business, nor scalable, nor maintainable.
Today, there are multi experience platforms that can connect to multiple back-end systems in a controlled and secure fashion for IT and corporate governance. The multi experience platform needs to be enterprise ready: that means secure, scalable and provide rock-solid API Management. For companies, the platform simply extends digital services from a web or mobile app to chatbots, voice control or AR and VR headsets. Once the platform is ready, and the first use case is delivered to the customers, the next one can be built on the platform easily as everything is set and scalable to the business needs. Another major advantage is that great multi experience platforms can easily and quickly add new services to existing use cases. Whether you want electronic signature, a blockchain, an AI engine, a workflow configurator, an authentication service or anything else – this will be once and simply implemented and is immediately available for all applications.
Data analytics, AI, and multi experience services will enable us to create scalable use cases for the enterprise world in a fast mode without programming.
Convergence of Content Management and Digitization enabled by AI
Now the convergence of content management and multi experience platforms begins. Content that has been used to feed and serve business processes will be analyzed, extracted and interpredet by AI to make it available for the business processes and to direct a workflow automatically to the right decision point or employee. That is the basis for contextual content management. Obviously, the backend integration of such systems helps multi experience platforms to speed up their ability to integrate to corporate IT. The process knowhow in combination with analyzed content makes completely new use cases possible that serve the end customer of a digitized business process better – as the decisions will be based on more and detailed corporate data.
The next big thing will not only be the mobilization or consumerization of business processes for employees, customers and partners, but also data analysis and measurable user experience to predict, advise and improve better services.
In the traditional procure to pay process (P2P) for example, the content management industry scanned invoices, matched them to orders and automated accounting processes. With AI services, advanced UX and dashboards, we can move on to anomaly detection to detect fraud in the process or compare purchase transactions across multiple ERP systems, compare prices, predict better cash management, and more. The value which can be generated by the analytic use of existing data and the new multi experience platforms with additional services can lead to a significant competitive advantage. The solutions can be implemented fast and easily without changing the corporate IT application landscape. Keep the ERP environments as they are and enable the digital journey for your company easy, fast and Corporate IT ready. Enhance the business value by the use of data analytics.
SAP just bought Qualtrics to get into Experience Management along processes that automatically deliver such a multi-experience platform in real-time across multiple backend systems to identify process bottlenecks or poor user experiences, improve business processes, and be one step ahead of the industry.
Data analytics, AI, and multi experience services on multi experience platforms will enable us to create scalable use cases for the enterprise world in a fast mode without programming, that are secure and have the ability to get an inherent feedback and improvement process to differentiate them from the competition. Feeding this with the content from the content management industry gives us the data to take well-founded decisions and generate value and results in short time.
As a side discussion, we at easy believe that this customer specific data is owned by our customer and not shared amongst others without consensus. As the data and the modeling will become the real IP to train and leverage AI Tools to build up the platforms of the future, it is key to make consensus decision where you put your data to train your systems from.