David S. Read

I routinely receive emails, tweets and snail mail from IT vendors that focus on how their solution accelerates the creation of business applications. They will quote executives and technology leaders, citing case studies that compare the time to build an application on their platform versus others. They will make the claim that this speed to release proves that their platform, tool or solution is “better” than the competition. Further, they claim that it will provide similar value for my business’ application needs. The focus of these advertisements is consistently, “how long did it take to initially create some application.”

This speed-to-create metric is pointless for a couple of reasons. First, an experienced developer will be fast when throwing together a solution using his or her preferred tools. Second, an application spends years in maintenance versus the time spent to build its first version.

Build it fast!

Years ago I built applications for GE in C. I was fast. Once I had a good set of libraries, I could build applications for turbine parts catalogs in days. This was before windowing operating systems. There were frameworks from companies like Borland that made it trivial to create an interactive interface. I moved on to Visual Basic and SQLWindows development and was equally fast at creating client-server applications for GE’s field engineering team. I progressed to C++ and created CGI-based web applications. Again, building and deploying applications in days. Java followed, and I created and deployed applications using the leading edge Netscape browser and Java Applets in days and eventually hours for trivial interfaces.

Since 2000 I’ve used BPM and BRM platforms such as PegaRULES, Corticon, Appian and ILOG. I’ve developed applications using frameworks like Struts, JSF, Spring, Hibernate and the list goes on. Through all of this, I’ve lived the euphoria of the initial release and the pain of refactoring for release 2. In my experience not one of these platforms has simplified the refactoring of a weak design without a significant investment of time.

Speed to initial release is not a meaningful measure of a platform’s ability to support business agility. There is little pain in version 1 regardless of the design thought that goes into it. Agility is about versions 2 and beyond. Specifically, we need to understand what planning and practices during prior versions is necessary to promote agility in future versions.

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I am excited to share the news that Blue Slate Solutions has kicked off a formal innovation program, creating a lab environment which will leverage the Cognitive Corporation™ framework and apply it to a suite of processes, tools and techniques.  The lab will use a broad set of enterprise technologies, applying the learning organization concepts implicit in the Cognitive Corporation’s™ feedback loop.

I’ve blogged a couple of times (see references at the end of this blog entry) about the Cognitive Corporation™.  The depiction has changed slightly but the fundamentals of the framework are unchanged.

The focus is to create a learning enterprise, where the learning is built into the system integrations and interactions. Enterprises have been investing in these individual components for several years; however they have not truly been integrating them in a way to promote learning.

By “integrating” I mean allowing the system to understand the meaning of the data being passed between them.  Creating a screen in a workflow (BPM) system that presents data from a database to a user is not “integration” in my opinion.  It is simply passing data around.  This prevents the enterprise ecosystem (all the components) from working together and collectively learning.

I liken such connections to my taking a hand-written note in a foreign language, which I don’t understand, and typing the text into an email for someone who does understand the original language.  Sure, the recipient can read it, but I, representing the workflow tool passing the information from database (note) to screen (email) in this case, have no idea what the data means and cannot possibly participate in learning from it.  Integration requires understanding.  Understanding requires defined and agreed-upon semantics.

This is just one of the Cognitive Corporation™ concepts that we will be exploring in the lab environment.  We will also be looking at the value of these technologies within different horizontal and vertical domains.  Given our expertise in healthcare, finance and insurance, our team is well positioned to use the lab to explore the use of learning BPM in many contexts.

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Given my role as an enterprise architect, I’ve had the opportunity to work with many different business leaders, each focused on leveraging IT to drive improved efficiencies, lower costs, increase quality, and broaden market share throughout their businesses.  The improvements might involve any subset of data, processes, business rules, infrastructure, software, hardware, etc.  A common thread is that each project seeks to make the corporation smarter through the use of information technology.

As I’ve placed these separate projects into a common context of my own, I’ve concluded that the long term goal of leveraging information technology must be for it to support cognitive processes.  I don’t mean that the computers will think for us, rather that IT solutions must work together to allow a business to learn, corporately.

The individual tools that we utilize each play a part.  However, we tend to utilize them in a manner that focuses on isolated and directed operation rather than incorporating them into an overall learning loop.  In other words, we install tools that we direct without asking them to help us find better directions to give.

Let me start with a definition: similar to thinking beings, a cognitive corporation™ leverages a feedback loop of information and experiences to inform future processes and rules.  Fundamentally, learning is a process and it involves taking known facts and experiences and combining them to create new hypothesis which are tested in order to derive new facts, processes and rules.  Unfortunately, we don’t often leverage our enterprise applications in this way.

We have many tools available to us in the enterprise IT realm.  These include database management systems, business process management environments, rule engines, reporting tools, content management applications, data analytics tools, complex event processing environments, enterprise service buses, and ETL tools.  Individually, these components are used to solve specific, predefined issues with the operation of a business.  However, this is not an optimal way to leverage them.

If we consider that these tools mimic aspects of an intelligent being, then we need to leverage them in a fashion that manifests the cognitive capability in preference to simply deploying a point-solution.  This involves thinking about the tools somewhat differently.

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InformationWeek Analytics (http://analytics.informationweek.com/index) invited me to write about the subject of process automation.  The article, part of their series covering application architectures, was released in July of this year.  It provided an opportunity for me to articulate the key components that are required to succeed in the automation of business processes.

Both the business and IT are positioned to make-or-break the use of process automation tools and techniques. The business must redefine its processes and operational rules so that work may be automated.  IT must provide the infrastructure and expertise to leverage the tools of the process automation trade.

Starting with the business there must be clearly defined processes by which work gets done.  Each process must be documented, including the points where decisions are made.  The rules for those decisions must then be documented.  Repetitive, low-value and low-risk decisions are immediate candidates for automation.

A key value point that must be reached in order to extract sustainable and meaningful value from process automation is measured in Straight Through Processing (STP).  STP requires that work arrive from a third-party and be automatically processed; returning a final decision and necessary output (letter, claim payment, etc.) without a person being involved in handling the work.

Most businesses begin using process automation tools without achieving any significant STP rate.  This is fine as a starting point so long as the business reviews the manual work, identifies groupings of work, focuses on the largest groupings (large may be based on manual effort, cost or simple volume) and looks to automate the decisions surrounding that group of work.  As STP is achieved for some work, the review process continues as more and more types of work are targeted for automation.

The end goal of process automation is to have people involved in truly exceptional, high-value, high-risk, business decisions.  The business benefits by having people attend to items that truly matter rather than dealing with a large amount background noise that lowers productivity, morale and client satisfaction.

All of this is great in theory but requires an information technology infrastructure that can meet these business objectives.

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