From IT Transactions with BI to IoT Interactions with AI An argument for a ‘Mid Office’ architecture
Originally published at https://www.constellationr.com/blog-news/it-transactions-bi-iot-interactions-ai-argument-mid-office-architecture
Analyst: Andy Mulholland
Online Web Based Business showed first retail, and then, many other sectors, that Internet ‘location’ was rapidly becoming more important than the physical location in attracting business. As Internet based business expands and transforms with IoT then understanding the concept of ‘interactions’, rather than the format of IT based ‘Transactions’, becomes necessary. The Enterprise orchestrates IoT event ‘Interactions’ from the market into an the fastest optimum response using its internal IoT assets is the new competitive winner.
Each stage of development of Internet based capabilities has increased the focus on winning business through smarter competitive Internet connected interactions. The recognition of the differences between activities and technologies of the so-called ‘Front Office’ versus the ‘Back Office’ become even more apparent with the introduction of IoT.
A brief reminder; The distinction between Front and Back Office is an important one, broadly defining the difference between the external revenue creating activities and the internal operating efficiency/costs of operating the company. Prior to the year 2000 competitive status focused almost totally on reducing the cost, and improving, the efficiency of internal operating processes usually with ERP. Front Office as a term meant little more than defining the role of the operating departments of Sales and Marketing. The technology used by the Front Office such as the original CRM, or Customer Data, applications were operated from the internal Back Office IT applications and Systems.
The Architecture of IT Enterprise Applications integrated through EAI Middleware created the business model, and the technology (IT) skills, that dominate most Enterprises. The mantra of ‘do more of less’ reducing both products, and operating processes to gain volume pricing economies for goods undergoing conventional physical distribution was the business transformation competitive game changer of the late 80s into the 90s.
Since 2000 there has been a growing use of Internet based technologies to engage with, and win, both customers and orders, by increasingly flexibility in supply to match the buyer’s criteria. The path to 2016 is one of increasing ‘agility and optimization’ of responses to Internet connected ‘opportunities’ to win business. The concept of ‘the long tail’ with its increasing number of low volume products is well on the way to becoming the norm of mainstream business.
Add to this the Cloud revolution of supplying technologies as ‘Services’ and the foundation for the revolution into the Digital Services economy is established. But Services, both in selling and supplying call for a close alignment between supply and demand, coupled to huge flexibility, or customization, of the product.
IoT is not merely the current IT Transactional Back Office model with more Internet connections, it’s the true enabler of the ‘Agile Enterprise’ Business model. As an example; Lean Manufacturing should define an IoT Architected Enterprise business model based on supplier/customer Internet Connectivity to ‘read and react’ through Interactions to Orchestrate an Agile optimization of ‘real time’ opportunities.
The obvious IT approach of adding increased IoT sensing to optimize the sub set of internal Enterprise processes that apply to the act of manufacturing is not IoT Transformation. Whilst there is no doubting the benefits of the increased efficiency brought it is incremental improvement to the current Business model using IT Applications. This is not the Transformation of the Business model that the CEO of General Electric, and others, has been discussing and presenting at Business conferences round the World.
So what’s the problem? After years of developing best practice architecture and deployment IT staff find it difficult not to try to apply their experience and expectations to IoT. (In contrast business managers who are less concerned by the technology seem to find it easier to grasp the Business value). To understand IoT and its differentiation from IoT is made easier by grasping two simple basic ways differences; the first, (and the title of this blog), is the difference between IT Transactions and IoT Interactions; and the second is the dimension of Time, or Timeliness, connected to when and how data is used.
To define IT Transactions is to recognize that the majority of IT Enterprise Applications are deployed to register that a transaction has taken place by the creation of a data record. This data record is a known, defined outcome used to design an application process and required inputs simply to ensure that the Data record will conform exactly. Time stamped, State’ is required to ensure that multiple users have the latest and correct copy of the Data record to use and update.
Data Analysis comes as at a later Time, looking for correlations between the various data records and their formats that where not established in the original records. In the relatively stable World of the 90s continued honing of operating efficiency with the business intelligence gained from Analytics ensured a continuous competitive edge was maintained.
Contrast this with the ability of IoT to create ‘insights’, or outcomes that could not be reliably predicted. IoT makes use input sources that have previously been inaccessible from a huge range of low cost sensors that together provide a continuous picture of events and activities as they occur. And, perhaps most important of all, the data can be used in time frame to optimize reactions as the events and activities are happening.
IoT creates value from orchestrating the ‘read’ of spontaneous ‘Interactions’ into ‘Insights’ that a business can make a ‘response’ to in a ‘Timely’ manner to gain a competitive advantage. The resulting ‘Agility’ in optimizing enterprise responses and resources, including suppliers, into a lean flexible competitive business creates the transformation of business models.
The ‘Front Office’, which was largely untouched by the IT revolution of the 90s is where this transformation is centered. The ‘Back Office’ will continue to require the internal transactions operation and recording for commercial and compliance purposes. The BIG question is how the Front and Back Office will integrate, and even more importantly how does this create an ‘Agile’ Enterprise.
The ‘Agile’ Enterprise has the potential to change not only how business processes are improved but also how modern workers can make better informed decisions by providing better ‘realtime context’ across the Front and Back office systems. Companies such as Abra uses Artificial Intelligence approach to an age-old challenge — how to increase the visibility of process changes – by helping visualize enterprise business process using data from transactions systems in the front office with data generated from IoT assets in the back office.
There is a potential answer to use as a ‘draft’ model and it comes from the Financial Sector. Digital markets, and rapid deal optimization using ‘’real time’ market data feeds closely resemble the expectations of Digital Business with IoT. The Financial Industry has found it necessary to introduce the concept of the Mid Office to integrate and operate the Front and Back Offices successfully.
In Financial Trading companies the Mid Office is responsible for risk management, setting the rules, and overseeing trades being successfully transacted in a compliant manner. The Front Office of any Digital IoT Business model will require a similar support role and will need to consider the concept of the Mid Office in their Enterprise.
The Mid Office is also likely to be the home of Artificial Intelligence, or AI, as the ‘intelligent hub’ modeling the Enterprise and continually updated with data and information. In the case of a Lean Manufacturing Enterprise then internal IoT data monitors resources and assets, whilst external IoT monitors the market, supplies, and suppliers. Here AI, unlike BI, will read and react to events, trends and activities in time frames that allow intervention to optimize opportunities.
Studying the Financial Industry and the development of the role of the Mid Office as the Intelligent Operational center of that integrates the internal and external operations provides much to interest Business Managers who are considering the strategic development of their Enterprises business model.
Reltio a provider of modern data management Platform as a Service (PaaS) enables what they call the ‘the next wave in enterprise applications’. The Reltio Cloud PaaS contains built-in Master Data Management (MDM) for data reliability, traditionally only viewed as a Back Office function. They then combine transactions and interaction data at big data scale and have used added Commercial Graph technology to intelligently uncover relationships between entities providing a foundation for front-office facing business applications.
Relto provides an interesting example of bringing the Front and Back Office together in what they call data-driven applications. The bringing together of IoT, and business usersin concert with IT’s data management of a single reliable pool of data is a hugely important next step for many Enterprises. Get it right and it makes immediate business value out of many current individual activities. Getting it right also lays the foundation for analytics and AI with machine learning to be applied ushering in the new era of capabilities that make up an Agile Enterprise.