Semantic BPM – epilogue

On this reflection we analyzed the current challenges companies are facing to manage business processes. Currently people are fighting against the meaning of things. Knowledge is no longer in procedures, in flowcharts, is spread across systems, sensors and streams. Knowledge is not anymore inside of company boundaries.

People interaction connected to companies are changing or are about to change as quickly systems to socialize are spreading. You cannot stop this paradigm. You can block social iteration for a while, but as new generations start working in the company you will need to adapt because these new bright lads don’t know how to work differently. There will be no regression.

In part one we saw that people want information that systems cannot interpret because questions are put in natural language.

In part two we discussed the paradigms of ontological management and how it can help to overcome the challenges outlined above, but it must be adaptive, dynamic, and evolve as organization domain changes. Ontologies cannot be a one time snapshot.

In part three it was defined a model for process, domain and organization ontology discovery.

On this last article we integrate semantics on business process management cycle.

So far we focused on a framework to build ontologies for process, domain and organization and how it can support enterprise architecture.

  • Process ontology: Identifies all the artifacts that describe a process, regardless of whether it is structured or not . It allows building clearly and unambiguously all process elements, linked with the domain ontologies that specify enterprise concepts,  as well as the business rules,  roles, outcomes, and all the other inter-dependencies.
  • Domain ontology: its not a glossary of terms, is what defines the company sphere and represents what the company does. This ontology provides vocabulary of concepts and their relationships, about the activities performed and on the theories and elementary principles governing that domain.
  • Organizational ontology: Identifies who participates in the work executed and how people are connected through the work and responsibilities assigned to them.

Ontology construction and its maintenance are beyond the scope of these articles series, but these references are a good starting point [20], [21].

As companies increasingly rely on information systems to run their processes it is necessary that systems provide semantic capabilities that allow them to use and apply ontologies, thus becoming intelligent. As already highlighted beforesystems still do not have fully developed intelligent capabilities to interpret information. Continue to be mere repositories of information in relational databases, but do not allow people to get the data they need to work and to reason. Paradoxically, systems turn out to be a barrier to understanding the enterprise as a connected system, unable to capture the characteristics of the organization in various dimensions: processes, domain and organizational.

As  dominance of unstructured work increases, integration of ontological management in enterprise architecture becomes more important for knowledge management challenges.

In 2009 it was already pointed out [22] the rise of knowledge management (although Drucker predicted by the 60’s !), a trend coined under the term adaptive case management. As pointed out by Deborah Miller [23] today with the growth of unstructured work people have to adapt to the unexpected, overcome challenges and achieve the unpredictable nature of our activities to achieve our objectives, management in this context, human judgment, external events and business rules do not determine the paths through a pre-defined (as a process flow) path. Rather, these factors determine in real time the activities that must be performed.

One of the key factors that support knowledge management is collaboration, but collaboration at its most intrinsic form is full of sources of waste. In the scope of ontology management two categories are worth identifying:

  • Interpretation: Time lost interpreting artifacts and it’s concept;
  • Research: Time wasted searching for information and their intra-relationships.

That is why the ontology management plays a key role allowing people obtain artifacts they need to work with, business rules, and remaining content in a facilitated manner.

How Ontology management integrates with BPM

The Business Process Management is usually based on these simplified four stages. This model is independent of the nature of the process that is running: structured or unstructured. I still don’t believe that BPM does not apply for unstructured processes.

BPM Cycle

Design phase: It defines how the process is going to be executed. In a structured process includes the process model everybody will have to follow. In an unstructured process, the process is constructed in real time, people define the set of actives and the information they need to work with.

At this stage the existence of a pre-defined ontology supports the understanding of the nature of the tasks that must be performed, and the nature of the concept of each informational entity. Thus it eliminates the ambiguity of natural language usage to the detriment of the concepts that are part of the ontology that is being used (process, domain, or organizational). The process model construction supported by an ontology can later be used during automatic Web Services linkage [26] if the process is automated all the elements that describe the process can be constructed in a format capable of being interpreted by machines, using for example XML. Another advantage is the possibility of reuse process models something that is a reality on adaptive case management.

Implementation: SOA is here for a while but companies struggle to connect seamlessly systems. One of the biggest challenges of adaptive case management systems is how they address connection in real time with data stored somewhere. A user cannot figure it out or manage to connect to it.

To make it possible endless connection capacity, it’s necessary to semantically describe all aspects of the services that are available through the interfaces. The standard WSMO [28] sets out how services should be described.

The process of building an ontology to describe a particular context is usually time consuming. In order to facilitate the introduction of ontological concepts, especially those that are internationally accepted in a particular industry WSMO was designed to be modular to the point of importing existing ontologies. The WSML [29] an extension of WSMO that defines a formal language to describe ontologies, goals, Web Services, semantically and a model for managing different language variants encompassing both logic descriptions as logic programming.

Still it’s possible to exist duplicate services, Semantic Web Services provides the following additional benefits:

  • Discovery of Web Services: Web Services are usually stored in a registry in order to be discovered, but with semantic capabilities it’s possible to prevent duplication and ambiguity;
  • Process Automation: Putting the process on execution mode involves the translation of all the artifacts that defines it. If there are no process models and Web services that can be reused, they are created and stored in the shared registry, otherwise it’s made ​​the discovery and connection to the process models (or process models parts) when the process is first installed or as you are execution it in adaptive case management mode. It is not necessary to make adjustments on message communication protocols, transport, security, because these features are supported automatically.

Execution: Under a semantic approach services are automatically discovered, linked to activities that invoke them in real time as opposed to a classic design highly coupled used specifically for the particular implementation of a process.

Analysis and monitoring: Both the analysis and monitoring use predefined reports or dashboards, thus limited to fixed content. Semantic Business Process Management allows users to search and correlate information dynamically supported by data recording semantically annotated by a system engine put in place for execution. Despite bottlenecks identification (tasks running more than once), workload balance and KPI’s provide important information about execution and improvement opportunities, the dawn of running unstructured processes or a bend between structured and unstructured, where execution is driven by events, questions, curiosity and outcomes is particular difficult to extract information to carry on our daily activities supported by predefined control mechanisms. People cannot way anymore one week to get hands on the data or an app than needs to be developed for a special purpose.

One last thought. Google Wave the trigger of this articles series is on read only mode. Is no longer supported by Google. Funny how concepts evolve.

References:

[20]  – Tasks for Ontology Design and Maintenance – Domenico Lembo, Carsten Lutz, Boontawee Suntisrivaraporn

[21] – Techniques for Ontology Design and Maintenance – F. Baader, R. Bernardi, D. Calvanese, A. Calì, B. Cuenca Grau, M. Garcia, G. de Giacomo, A. Kaplunova, O. Kutz, D. Lembo, M. Lenzerini, L. Lubyte, C. Lutz, M. Milicic, R. M¨oller, B. Parsia, R. Rosati, U. Sattler, B. Sertkaya, S. Tessaris, C. Thorne, A.-Y. Turhan

[22] Using technology to improve workforce collaboration – James Manyika, Kara Sprague and Lareina Yee

[23] How Adaptive Case Management Helps Businesses Overcome Challenges and Improve Performance – Deborah Miller

[26] Service-Oriented Architecture Ontology – The Open Group – ISBN: 1-931624-88-7

[28] Web Service Modeling Ontology – Cristina Feier, John Domingue http://www.wsmo.org 

[29] Web Service Modeling Language – J. de Bruijn, H. Lausen, R. Krummenacher, A. Polleres, L. Predoiu, M. Kifer, D. Fensel http://www.wsmo.org .

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Nothing will be the same

The major change will be driven by cloud infrastructure an ubiquity computing and system integration. Execution will be result oriented and data driven. Automation will be supported on apps that allows to execute the task on a self service mode. The user does not need to know how it works. He is sure that will work because cause effect linkage in systems is build in.
Ontologies providing meaning to the data manipulated thus no one needs anymore to learn the company domain and environment meaning and from it’s connected stakeholders because is automatically translated into other business environment.
People will be over connected naturally without the need to request for connection.
There will not be anymore information and intelligence. There will be knowledge.

Semantic BPM part three

In part one, I looked at the limitations of current enterprise systems to build a social process ecosystem, in order to  architects, managers and company employees can understand what is the business environment, what means the concepts used within the organization and what is the business domain (context) all about.

In part two I introduced the importance of how unstructured work increases the importance of semantics, and defined a model for Semantic BPM.

To create a domain ontology is necessary to apply a set of techniques used in social network analysis. These techniques are based on the same mathematical principles of algebra as described in [15]. After all informational entities are identified it can be presented through affiliations with business processes using an incidence matrix.

In this example, let’s consider an accident management process executed inside of an insurance company.

 

Customer

Policy

Contract

Accident

Invoice

P1

1

1

1

0

0

P2

1

1

1

1

0

P3

1

0

0

0

0

P4

1

1

1

0

1

This matrix is intended to identify the relationship between processes and informational entities, is not intended to specify the type of operation that is performed on top of the informational entity such as in a CRUD matrix.

In this case we can see that the process P1 only handles informational entities related to Customer, and Insurance Policy, while the P2 process handles all entities Process P1, plus Accident.

It is important dot not confuse the concept of Informational Entity: any person, place, concept, thing, or event in the context of the business, about which information is necessary to keep the informational attributes of the entity itself. For example, the informational entity Customer has the attributes: “Number”, “Name”, etc..

One of the conclusions is that matrix representation can easily identify which business processes manipulates entities, making it easier to create a meaning.

From the above matrix it can be derived two adjacency matrices:

One that relates the intensity of the connection between the processes and the shared informational entities:

 

P1

P2

P3

P5

P1

3

3

1

P2

3

2

2

P3

3

2

1

P4

1

2

1

This matrix identifies the intensity of the data exchange between processes through access made to the informational entities, in other words shows the number of informational entities that are related to particular process and can be represented in the following graph:

In this graphical representation it can be concluded that the processes with more relationship intensity is between the P1 and P2 and P1 and P3. In the first case both processes share informational entities Customer, and Insurance Policy. The same method can be used if instead of a Process you have a Case (for Ad-Hoc processes).

Other matrix relates the intensity of informational entities together.

 

Customer

Policy

Contract

Accident

Invoice

Customer

2

2

1

1

Policy

2

3

2

1

Contract

2

3

2

2

Accident

1

2

2

0

Invoice

1

1

2

0

This matrix identifies whether a relationship exists between the informational entities and how many processes are used simultaneously. In this example the entities Insurance Policy and Contract have a strong relationship because they are both found in three processes.

The reasoning we have followed allows us to make the same kind of analysis with Activities and Tasks. What may be seem like a mere mathematical exercise is very important as we intend to involve hundreds or thousands of people to work effectively, self-directed, and socially motivated. Although structured processes theoretically force participants always to perform the same steps with the same sequence we know that these artifacts do not always have the same meaning for people. With the emergence of tools that allow Ad-hoc process execution is extremely important for people that access/manipulate certain artifact being sure of it’s meaning, otherwise we are opening the door to knowledge chaos because people with his human nature sometimes like to designate differently the same concept. This finding also opens a way for the need to define a data repository model, the ontological foundation, that is outside of the scope of these articles series, still this reference can be usefull [24].

Returning again to the hiring process flowchart example, let’s consider what we have here two hiring Ad-hoc processes excuted at different times.

 

Acknowledge application

Analise application

Examine Process

Evaluate

application

Send

application

Apply for job

P1

P2

1

0

1

0

0

1

1

1

1

0

0

1

It is clear the importance of getting the information structured this way. Two instances present differently the same concept: Application / Process. What is the dominant concept in the organization? What name should be adopted? If we have to run a report how to do it?

Using the same principle, we can analyze the dependencies between process participants. This aspect is important because through a analysis of this type we can:

  • Understand dependencies and the dependence size of the participants, ie the effects of human socialization itself;
  • If the process is executed between the ones that should involved in execution or is being executed by the ones that don’t have knowledge to do it;
  • Have a clear idea if IT supports the data flow, if there are too many hand-offs, if people depend heavily of a particular individual, if the transactions are balanced or some leveling is necessary, people are qualified to perform the job;
  • What are the knowledge sharing patterns within the organization.

All this can be achieved without having to make analysis to organizational charts and process swimlanes. Stabell and Fjeldstad [17] define a clear focus on the need to answer the questions, one of the most interesting references about how work can be executed under the knowledge management umbrella. If we look at the intrinsic nature of knowledge work there is a considerable amount of intangible communication flows such as: advice, information sharing, which are activities rarely found in flowcharts.

Thus we can understand if we look from a social perspective the roles that interact in the process so you may have an idea of organizational network analysis. This analysis may include roles performed by partners, suppliers and customers, truly end-to-end.

Returning to our initial example, considering a matrix that relates processes of an insurance company and the participants involved in these processes.

 

Contact Center Front office

Customer Account Manager

Contact Center Manager

Accident Manager

Contact Center Back Office

 

P1

1

1

1

0

1

P2

1

1

0

0

1

P3

0

1

0

1

1

P4

0

0

0

0

1

If we make an analysis using a intra dependency matrix between participants we get:

 

Contact Center Front office

Customer Account Manager

Contact Center Manager

Accident Manager

Contact Center Back Office

 

Contact Center Front office

2

1

0

2

Customer Account Manager

2

1

1

2

Contact Center Manager

1

1

0

1

Accident Manager

0

1

0

1

Contact Center Back Office

2

2

0

1

Using a graph, we get:

The graph provides these insights:

  • Back Office is the participant who supports most of the information exchange;
  • Back Office, Customer Account Manager and Front Office rely heavily on each other;
  • There is not much interaction between the Accident Manager and the remaining participants (should be?).

From a global viewpoint and applying techniques of social network analysis it’s possible to identify:

  • Do we have “stars” in our workforce?;
  • If there is a strong coupling between the connections (and if this coupling) is aligned to the nature of information exchange [18]?
  • Who plays a particular role? Is this according what the enterprise thinks it’s best?
  • What are the communication channels between individuals involved and who is more dependent on whom?
  • Do we have balanced connections?

The answer to these questions leads us to conclude much about the nature of the alignment of human resources and business processes.

In part four I will present a wrap up and final thoughts.

References:

[15] Theory and Method of Social Research – J Galtung, Columbia University Press, ISBN – 0-231030-88-6

[17] Configuring Value for Competitive Advantage: on Chains, Shops, and Networks – Stabell, C. and O. Fjeldstad (1998). Strategic Management Journal 19

[18] An Ontology Framework for Semantic Business Process Management – Martin Hepp, Dumitru Roman

[24] Ontology reasoning with large data repositories – Stijn Heymans, Li Ma, Darko Anicic, Zhilei Ma, Nathalie Steinmetz, Yue Pan, Jing Mei, Achille Fokoue, Aditya Kalyanpur, Aaron Kershenbaum, Edith Schonberg, Kavitha Srinivas, Cristina Feier, Graham Hench, Branimir Wetzstein, Uwe Keller – Ontology Management – Springer – 978-0-387-69899-1

Semantic BPM part two

In part one, we have looked at the limitations of current enterprise systems to build a social process ecosystem, in order to  architects, managers and company employees can understand what is the business environment, what means the concepts used within the organization and what is the business domain (context) all about.

I also created the quest of establishing a dynamic method for structuring business ontologies, taking into account that usually there is a misalignment between the enterprise architecture and execution of business processes, especially in an era when more and more processes are no longer structured as it used to be (described in flows, in documents, procedures).

In this part we define a method for discovery of processes semantics and how it contributes to the enterprise ontological management.

Unstrutured work increases the importance of semantics

The dawn of “Case Management” amplified even more the importance of building enterprise ontologies.

There are several synonyms for “Case Management” [39] like:

  • Unstructured work;
  • AD-HOC process;
  • Dynamic Case Management;

I prefer to use the term AD-HOC process because is much more comprehensive, the name “Case Management” seems to apply only to managing a dossier with files inside it, as happens for example in law firms, as well the terminology used seems to be very restrictive. The term AD-HOC is more related to the need to manage creative thinking and empowerment and I will stick to this definition.

Executing AD-HOC process may be supported in portals or wikis. This is not anything new because the technology has been available for long (you can do it with e-mail). For example using the enterprise portal and especially in process mashups [2], collaborating like in the example provided before using Google Wave.

While acknowledging that socialization has brought advantages in how people can collaborate to execute some task work being able to work together in collaborative environment, still lacks a method for ultimately people “understand” the artifacts they are dealing every day. This is particularly important because even despite for managers, process experts, there is a common dictionary of business concepts, for the other people, often these concepts remain abstract affecting the way work is performed.

Some years ago if we need to identify the relationships between business processes, we had to rely on graphical representation such as prescribed in SAP Modeling Handbook [11], but with the advent of AD-HOC process the classical representations are compromised since AD-HOC processes are not even mapped because they are executed seeking to achieve a particular outcome. The dynamics of the business world is increasingly running around unpredictable work requires a dynamic model of ontology representation, because employees manage informational entities (artifacts or objects) that have to be clearly defined, otherwise they are not sure the they are manipulating.

People are often confused with the concepts of output and result of a process, some people think this means the same but they not. To clarify what it is it’s worth revisiting the definition given by Arthur R. Tenner and Irving J. DeToro [12] back in 1996!

Output – Ability of the process comply with all applicable specifications.
Result – Ability of the outputs meet customer’s needs.

To understand the changing paradox processes can be executed, let us consider a process to select someone to fill a job vacancy within the Financial Division. For such a position there is no standardized process because it is not appropriate to the type of position he want to hire.

The person carrying the responsibility to do it must:

  • Define activities required to reach the desired result – hire someone.
  • Identify the informational entities (the artifacts, objects, or data if you want) that are manipulated during the execution of the activities, for example, Candidate, Interview, Recommendation, Qualifications, etc.

In the figure below we can see how a BPM tool, can let the user define what we wants to accomplish without any kind of flowchart.

AD-HOC HR Process

Each activity must be associated with the informational entities that will be manipulated at runtime.
However, when the process is already being executed is identified the need to add one more activity , in this case a review from a Human Resources Department. For a BPM tool with advanced capabilities that is not a restriction.

Inserting a new task dynamically

Today there is no single way to perform the work. Human judgment, unpredictable conditions, business rules determine which activities should be performed, designed in real time.

Peter Drucker [37] stated that working in the knowledge era means:

The first questions to increase productivity and work smarter, have to be: What is the task? What we are trying to achieve? Why do we have to do this anyway?

The model

The model for semantic business process management is presented below built using a UML class diagram because is the ultimate abstraction and it applies to every industry sector and process type. This model could not have been stutured without the contribution of André Brandão and João Graça [13].

Semantic BPM model

This model is based on the principles described in algebraic graph theory.

A network is based on the following principles:

It is a set of nodes and arcs. In this case the nodes are represented by processes and arcs representing the relationships between processes.

Process network
In this example there are four processes. Processes P1 and P2 and P1 and P3 are connected, P2 is linked with P3, P4 is connected to the process P3.

Each arc expresses a relationship. In this particular example of a process network as opposed to a social network there is only one type of relationship, which can be called “connected to”. In personal social network you can assign different relationships types among people such as: “work with”, “family” and I believe there is a temptation you can assign different names to the relations between processes such as: “support”; ” supported “,” variant “, but this classification complicates the reasoning of the relationship model between the processes themselves. So let’s stick with the limitation we can only classify the relationship as “connected to”.

Processes can belong to groups. You can designate groups of processes that you want and you can create groups of groups of processes.
Today business processes are grouped together according to many models:

  • According to a standard business framework: SCOR, eTOM, UBPF,ITIL;
  • According to a industry framework like airport management divided into non-aviation and aviation;
  • According to a framework defined by the company;
  • Without any specific rule.

The processes are composed by activities and tasks without it they did not exist. Processes can be structured (those who have to be repeatedly executed in the same way, often represented by flowcharts if necessary) and unstructured have a particular sequence of activities that were not previously predefined. Process groups can be grouped together. It’s possible to have groups of processes and groups of groups.

Tasks have participants (those who perform the work) and the processes have managers (someone responsible, not the classical definition of process manager) the same is true for process groups, although this condition does not always apply. For those who argue that in AD-HOC processes such definitions does not exist, there may not be formally an owner, as in traditional approach to process management, but someone oversees the progress and the outcome achievement.

In a matrix form (represented in a binary adjacency matrix), using the principles of mathematics it possible to represent algebraic relationships in this way:


The binary value 1 between two processes means that there is a relationship between them, the binary value 0 means no relationship exists between the processes.

What matters here is not discussing an abstract representation of the matrix because it is governed in accordance with the principles of algebra, and secondly the representation can be stored in a database. Therefore we will not make analysis about foundations of the theorems of mathematical representation. The important part is that you can do with it.

The creation of a true process social network, allows to build an ontology, must being able to answer such questions automatically:

  • What we do inside our organization?
  • How people collaborate?
  • What is the meaning of each logical domain in the organization?
  • What is the relationship between intra-existing processes?
  • What is the nature of the relationship between the processes?

These questions are also valid for AD-HOC processes that are created automatically the first time and relates with any object.

As we will see later this model allows to understand the relationship between the informational entities starting from the relationship between enterprise interactions.

The creation of process ontology is valueless regarding such representation. More importantly the possibility of building a process ontology, is to build a domain ontology, things, business entities, enterprise concepts.

All processes have informational entities: Customers, Complaint, Order. These entities are managed and over a certain life cycle as the processes are being executed: they are created, read, updated, and deleted. The concept and interpretation of each of these informational entities are the biggest challenge facing organizations to succeed in building a domain ontology.

On the other hand with the emergence of AD-HOC processes in which people get the informational entities that need to work and execute process instances, if there is not a clear idea about the meaning of each thing, creating barriers to “knowledge management” and “learning organizations”.

This example adapted from [14] is symptomatic of what I mean. Although the authors focused much on the issue of process modeling, representation conflicts, and explanation of the graphical representation, what matters is what is your interpretation when dealing with information, the meaning of each thing, each entity.

Semantic conflicts in the real world

To create a domain ontology is necessary to apply a set of techniques used in social network analysis. These techniques are based on the same mathematical principles of algebra as described before. I will explore it on part 3. But if you can you can move to the epilogue.

References:

[2] Process Mashups: Helping Project Teams Put the Pieces Together. http://www.ibm.com/developerworks/rational/library/edge/09/jun09/processmashups/

[11] SAP Modeling Handbook –
http://wiki.sdn.sap.com/wiki/display/ModHandbook/Level+2+Process+Groups

[12] Process Redesign: The Implementation Guide for Managers – Arthur R. Tenner e Irving J. DeToro,  Prentice Hal – ISBN – 0-201633-91-4

[13] Social networks in enterprise world – POSI XII – Alberto Manuel, André Brandão, João Graça.

[14] Semantic Business Process Management – Jorg Becker, Daniel Pfeiffer, Thorsten Falk, and Michael Rackers do livro Handbook of Business Process Management, Springer, ISBN – 3-642004-15-6

[37] Tasks, Responsibilities, Practices – Peter Druker – Harper Paperbacks – ISBN 088-730-615-2

[39] The anachronism of acronyms – Gary Comerford – http://process-cafe.blogspot.com/2011/02/anachronism-of-acronyms.html

Semantic BPM – Part One

This is a remastered article written in 2010 on Redux blog that unfortunately was deleted with some very interesting comments that were recovered later by Theo Priestley and I copy it to the comments. Still there is copy on a old personal blog I used to write before.

This remastered series was finished in April this year and I’m translating it to English. Since then, some of the concepts suffered some evolution but I decided to keep what I written before in order to not change the first article concept.

The article have four parts. This is the first one. This is the second part. This is the third part. This is the epilogue.

Introduction:

The interest in this field started two years ago when Google launched product that did not succeed in the market: Google Wave. When it was launched in mid 2009, it was considered a threat to Facebook, because it allowed to manage our online conversations inviting or being invited to participate (widespread of co-creation). With Google Wave it was also possible to add/share files, images and other content. At the time I thought this tool could be used in business environment to collaborate with people, discuss ideas and enable as a tool business processes management. Gartner introduced the need for BPM system vendors to support collaboration among users – User and group collaboration “, ” Social BPM “had born.

Curiously few months after Google announcement (October 2009) SAP introduced a prototype which showed the integration with of a product called Gravity . Later, in February 2010 this prototype evolved into the SAP StreamWork. Other companies followed the same steps with other approaches: IBM introduced IBM Blue Works, ARIS Alignspace , followed by others. In 2011 there are already products like Appian Tempo and others like Hojoki  enabling activity streams.

In 2010 Keith Swenson summarized a very interesting set of definitions on “Social BPM”:

  • Clay Richardson Social BPM defined as: “Processes developed and improved through the use of social technologies and techniques”
  • Gartner says: “Social BPM is a concept that describes collaboratively designed and iterated processes”

Forrester added this definition although I do not understand clearly what is “social technology”:

  • “Processes developed and improved through the use of social technologies and techniques.”

This leads us to the topic of discussion, companies were constantly wrestling with the phenomenon of real-time collaboration.
Online information is becoming increasingly dynamic and the appearance of customer relationships in social networks enhance this phenomenon. These contents are richer, more dynamic, requiring more interaction and intensify these collaboration between the company and internal and external stakeholders.

The challenge is that as we headed for an increasingly connected world, the meaning of things we handle must have sense. It must have an interpretation. Enterprise ontology helps you find the meaning of things, but must be able to be as dynamic as the information flows on which we depend to carry out our work.

Today companies design and implement their processes supported by a multiplicity of systems. Duplication of data, concepts, lack of understanding on a specific area where the process runs remains a reality.

The same concept has different meaning for people who work within the organization or interact with it.

At systems level illiteracy continues to exist even with the SOA approach.

Business Intelligence continues to transform and correct the data that are scattered across operating systems and depend on human reasoning to interpret their meaning.

Increased collaboration between people requires that people know the meaning of what they are manipulating. Today the work ceases to be increasingly divided into streams, where people can see the significance of what they are doing. Increasingly, the nature of our work is oriented to the manipulation of informational entities, tasks that need to be executed, help requests, queries about stored info.

The challenge that I intend to achieve is the definition of a dynamic method of discovery and ontology management in order to enrich the knowledge about the meaning of things in business context.

An ontology can be managed in tools such as Protégé but is not guaranteed connection to the business processes definitions stored / executed in multiple systems, and therefore there is a very high risk of content obsolescence. Ontology construction tools as mentioned in [6] seems to be able to analyze a business domain without taking into account the business processes ecosystem and all existing relationships.

Process Management as it was thought reached the limit

I believe the title of this section be an infamy. But I believe that most of the people do not agree are in monolithic context . That’s fine. They are in denial.

Reality changes much faster these days. Today most of us are knowledge workers. Specially in service companies (in the industry this concept has existed for decades). It is curious that this cliché was introduced by Peter Drucker in the book Management: Tasks, Responsibilities, Practices and was reinforced latter by Toffler in the book Revolutionary Wealth: How It Will Be Created and How It Will Change Our Lives.

The first time I heard knowledge worker / knowledge management concept has in early nineties, when I read an article by Peter Druker in Harvard Business Review called Management and the World’s Work made me read the book by the same author quoted above, which was first published in 1973. People that advocates today that we live in the knowledge era, are 40 years late.

Imagine you are a manager and need answers to these questions. Prepare yourself. Take a deep breath and answer the questions below if you can (if you have trouble seek for help from a SQL or Oracle database administrator).

  • How many transports we did for Low Emissions Zone  in that we were fined by entering it with trucks that do not fulfill the norm EURO 4?
This question is best answered by Ray an operations manager; he has the answer in his head. Leave for now the database Administrator in peace.
  • When we are it performing transactions with the partner X, the operating licenses are valid?

Dear manager. Are you angry? All this could be resolved with Reporting Services, just build the example using SQL. SQL is a widely used non-procedural language, but is incapable of answer the doubts and dynamic questions that devastate our poor knowledge worker. As you already concluded, SQL answers always to the same questions, but predictive features are not available regarding the nature of the information that the user intend to obtain answer from.

If the “knowledge worker” want something more, or the query was not designed correctly the questions remain unanswered.

Another day at the bank the account manager was looking for a fund that had subscribed 5 years ago. The manager could not find it because the search was being made with “-” when the fund name is “Energy_Europa.” I even thought to myself: the fund disappeared. The bank got the money. In fact the search engine was not working correctly.

Let us focus the fundamental question: what kind of information that your company handles? Is there a way for this information being used among the people? Information is understood by your customers in the same manner as understood by your employees when they interact with your company?

Think deeply about this question. Sincerely do you believe that your data stored in a data center enables you to manage your business processes adequately? Don’t you agree that most of your data does not have meaning despite your Business Intelligence solution, the dashboards, the reports, specially on the new brave world of ACM where people are encouraged to build ad-hoc solutions using the data spread all over the systems?

What is the customer concept of for most of of the people? Is the business entity that pays the money for your products or is the consumer that uses it and pays it to your customers?

Under the empowerment paradigm a business user building a case how does it name the customer object? Where the customer table is accessed? Will other empowered user name the customer consumer, end user? Does a system have intelligence to suggest what is a customer  is? Does it knows how the company defines customer?

The use of tools for the deployment of ad-hoc process will also aggravate this issue. Remember when BPMS arose? Remember the promise BPMS would work in a layer above the existing systems in the company promoting it’s connection? What do you think AD-HOC process systems are? They are the first breach in BPM systems. We are coming back to the starting point. Several systems for business processes execution. Want structured? Infinitely repeatable? Buy BPMS. Want AD-HOC process capability? Buy other tool. We are back to the beginning because the agility promised by the BPMS in the reality never was achieved, because communication between machines was not developed sufficiently.

Systems and machines do nothing more than show and register information, when should be capable of show and register information about the operations performed.

Still ACM systems lack intelligence. Some imply building data models to use it, or let users freely used data in a chaotic way destroying reuse and pattern construction.

Ontology management

What are ontologies?
For me the best definition of ontology is:  “An ontology is a formal specification of a shared conceptualization” [3] .
Ontologies are methods that interpret natural language, human language to language that is interpreted by machines and vice versa, ie allows you to interpret the data that is stored and processed by the machines that we humans need to perform operations, analysis and decisions.

Use of ontologies for data search

Often analysts talk about of “Social BPM” as if it were the tools that allow various stakeholders to structure, talk , interact and exchange information, execute around a particular process, however the foundation of “Social BPM” is the ability to relate a network of processes and understand people,data, interconnections and dependencies like as a social network. Regarding this concept I would like to remember Conway’s Law [4]:
Organizations which design systems are constrained to produce designs which are copies of the communication structures of these organizations.

A network of processes is organized like as a social network.

This network can be your enterprise architecture, but it’s not presented like the old process frameworks. Despite being useful, on one hand these frameworks are good for reference only but on the other hand these are best practices approaches than limit your capacity to differentiate. On the bottom line people are getting acquainted to information circulating around need to perform work, due the deconstruction of the desktop station.

Each node represents a process. Relationships exist between each process represented by line segments. Within the circle, there are alive business processes. This type of representation has its roots in mathematical principles. However it seems very clear that current BPM/ACM tools do not apply this concept difficult to understand the relationships and understanding of business processes. Most processes that are designed/ executed in BPM/ACM tools, are stored in a repository with specifications attached and flowcharts, historic data, like a knowledge base. Hence, people are managing processes in a static way.

Remember this: If you try to modify an object/artifact of a business process do you have an idea of the impacts of than change? Or you don’t know just because you look to you process repository where everything is disconnected? And if you don’t have any specs or flowcharts, because that is not needed? Imagine you want to change a business rule that applies across the organization. Do you, the CIO, your personnel have the capability to do it without ruin the execution were that rule is used with past assumptions?

Process Network

Let’s return to ontology management. Re-examine the previous figure, instead of thinking in processes, think like this is a network of interconnected concepts. Like a language, like a brain.

There is another fundamental principle that must be internalized: ontology management will never be the an archive of information as a knowledge management system with indexing like a document management system or files in a computer. For example you can file a document with the name KPI’s specification in a directory called “balanced scorecard” and through a seach engine you can find it whenever you want (as long as the search engine is not the same as refered in the bank example) . You can connect manually to another document on “performance management”, but one of the main features of an ontology is that it is independent of the context in which a particular concept instance is. Ontologies are a way of relating concepts that are related through common domain, as liker entity relationship in UML class diagrams. But on this case we want to discuss it’s application on a business domain.

This implies that is necessary to develop a common vocabulary to use in process management, as well as a process for it’s management. This principle is very important because as more knowledge is transferred from our process network to machines that store all the data in each instance, increases the risk of not understanding concept meaning and retrieve the information we humans need to work with (remember the example of customer and end user). The aim of this vocabulary development is not to build a dictionary. It is building a network of relationships and provide a unifying element of the terms from different sources, especially when there are companies whose processes are shared between suppliers and customers or partners.

The model will be presented in the second part of this article.

References:

[3] Toward Principles for the Design of Ontologies Used for Knowledge Sharing – Tom Gruber http://tomgruber.org/writing/onto-design.pdf

[4] “How do Committees Invent?” Datamation. Conway M.E. http://www.melconway.com/research/committees.html.

[6] Ontological Engineering – Asunción Gómez-Pérez, Mariano Fernández-López, Oscar Corcho, Springer ISBN 1-85233-551-3, pages 109 – 153.