On part 1, I introduced the importance of social network understanding as the socialization of interactions is becoming a new working habit and as such classic control flow perspective analysis does not anymore provide information about how work is done.
On this post, I will explore important points to look for when performing Social Network Analysis (SNA).
Social networks have typically the following properties:
- Emergence: agents that belong to the network interact in an apparently random way. This feeling is amplified if there are many agents and / or there are too many interactions that make difficult to extract patterns. Emergence is all about separating the signal form the noise and make those patterns to emerge.
- Adaptation: enterprises, communities, exist confined in a particular environment that when changes it makes agents to react. Environment can be external, interaction with customers, suppliers, government agencies; influence like the publication of a new law or regulation or competitor movements as they enter in new markets or create new products or services. Environment can also be internal and its related to the way agents interact that is ultimately associated with how business processes were designed, how IT solutions were deployed, culture, hierarchy configuration and formal recognition of authority, just to provide some examples.
- Variety: Ashby, one of the father’s of cybernetics, defined the Law of Requisite Variety “variety absorbs variety, defines the minimum number of states necessary for a controller to control a system of a given number of states.” For an organisation, to be viable it must be capable of coping with the variety (complexity) of the environment in which it operates. Managing complexity is the essence of a manager’s activity. Controlling a situation means being able to deal with its complexity, that is, its variety .
- Connectivity: The way agents are connected and how those connections are aligned with the process type that was designed / being executed and the type of knowledge that is necessary to support operations (more about this alignment here). The existing connections will unveil the emergent patterns that are necessary to identify and understand behaviour under a social point of view (high coupling or loosely coupling between agents or group of agents).
On network types:
Most of the times when people refer to social networks they are expressing their beliefs on community networks like Facebook, subject expert groups like enterprise wikis. Although those are important network types, they do not express the nature of organization operations, because they do not record communication acts expressed on social activity, hence I will only concentrate on Coordination Networks.
A Coordination Network is a network formed by agents related to each other by recorded coordination acts.
Coordination acts are for example, the interchange of emails, tasks as design on enterprise systems or activity streams just to provide some examples. The above definition is an adaptation of  because it does not include the importance of coordination act that is related with the nature of work, rather the connection itself. The former is the important dimension related with business process management and will guide the remaining content.
Coordination acts is meant to be as defined (adapted)  an act to be performed by one agent, directed to other agent that contains an intention (request, promise, question, assertion) and a proposition (something that is or could be the case in the social world). In the intention, the agent proclaims its social attitude with respect to the proposition. In the proposition, the agent proclaims the fact and the associated time the intention is all about, recorded by the system, supporting the definition Coordination networks, which configuration that can ultimately be discovered, patterns emerge, using discovering techniques like for example process mining.
On analysis dimensions:
Social network analysis is not new. Actually, the first studies were done around the 50’s of last century. Its refinement stumbled around:
- Degree distribution: study connection number around a node of the network;
- Clustering: groups with connection density larger than average;
- Community discovery: measures alignment of connections regarding organization hierarchy.
There is an immense list of techniques to analyse each one of the above dimensions, that reflects the high maturity level of each method, but he drawback is that SNA analysed on each dimension alone can induce managers in the wrong direction. For example, studying community discovery can be important, because communities are a collection of individuals who are linked or related by some sort of relation. But carrying the analysis without taking into consideration the content of the conversation (coordination act) that drove the creation of the link is absolutely wrong, because the conversation is all about the way we humans work. I tend to disagree with other points of view from other practitioners that conversation does not matter (probably because they were influenced by Gordon Pask), only the network configuration. Conversation (the process) is the matter of study.
Social networks are self-organizing systems, but there are important patterns that emerge from the nature of the coordination acts that can be identified. Despite there are random factors and the type of patterns presented in most of scientific papers are based on graph theory and tend to be very simple compared with the reality (and hence maybe this is one of the reasons they are not taken seriously) it is the only way, as an abstraction, to understand agent behaviour. Pattern recognition is critical to align process type (from structured to unstructured), knowledge domain (simple to chaotic) and network type (central to loosely coupled). In order words, to infer trends and help humans to interact better regarding the role they play in the process ecosystem. Having said that, I would like to invoke Stafford Beer’s on models: “in general we use models in order to learn something about the thing modelled (unless they are just for fun)” .
Centrality is used to measure degree distribution. Centrality  is described as a process participant, business unit, group (a set of process participants or people) or an enterprise system (do not forget the machines) within the context of a social network. Centrality is also related with discovering the key players in social networks.
Some measures that can be used for Centrality are:
- Degree centrality: calculate how many links a node has regarding the remaining network nodes (commonly called network stars). Higher degree centrality means higher probability of receiving information (but does not mean it drives information flow inside of the network).
- Betweenness: measures the degree witch a process participant controls information flow. They act as brokers. The higher the value, higher is information flow traffic that moves from each node to every other node in the network. The importance of Betweenness in social network analysis is nodes with higher values stop processing coordination acts, will block information flow to run properly.
- Closeness: measures how close a node is isolated in the network compared with other network mode. Nodes with low closeness are able to reach or be reached by most of all other nodes in the network, in other words low closeness means a node is well positioned to receive information early when it has more value. Closeness measure must be supported on time dimension (see reference about the timestamp attribute on the coordination act exemplification), without it, is useless.
- Eigenvector centrality: used to calculate node influence in the network. Higher scores means a node can influence (touch) many other important nodes.
In order o put it all together its worth to consider the following self-explanatory picture :
There is a lot of noise around what is the best measure to perform SNA, as I learned at the User Modelling, Adaptation and Personalization Conference 2011 it’s time to put the mathematical equations aside and practice it’s application.
At this moment of time, there are plenty of ways to measure network centrality, but somehow they neglect that those algorithms are not appropriate regarding the type of business process / information system interaction played. For example, Eigenvector centrality measure is important in unstructured processes, where the path is defined on instance mode and it is necessary to create a team and involve others as the process progress. Once SNA does not analyze the process type, only about agent relation, if applied analyzing a procure to pay process (highly structured process type) it’s useless and can damage results interpretation, because on this case, every agent, every process participant receives and process information basically the same way to achieve the same outcome every same day. Maybe this is the reason why is not yet taken more seriously, because these days the process is all about social interaction and it cannot anymore be analyzed naively taking into consideration the dispersion, complexity and interdependence of relationships, something that can also be applied on IT requirements elicitation or IT system operation , which allows to understand communities interaction in order to support emerging and unique processes under a techno-social systems approach .
 – Design and Diagnosis for Sustainable Organizations – Jose´ Pérez Ríos – Springer – ISBN 9783642223174
 – Large Scale Structure and Dynamics of Complex Networks – Guido Caldarelli; Alessandro Vespignani – World Scientific Publishing – ISBN-139789812706645
 – Enterprise Ontology – Jan Dietz – Springer – ISBN – 3540291695
 – Complex Adaptive Systems Modeling – A multidisciplinary Roadmap – Muaz A Niazi
 – The Brain of the firm – Stafford Beer – Jonh Wiley & Sons – ISBN – 047194839-X
 – Discovering Sets of Key Players in Social Networks – Daniel Ortiz-Arroyo – Springer 2010
 – José L.R. Sousa, Ricardo J. Machado, J.F.F. Mendes. Modeling Organizational Information Systems Using “Complex Networks” Concepts. IEEE Computer Society 2012, ISBN 978-0-7695-4777
On the previous article about A Social Platform Definition, I presented a framework about the elements of such Platform. The following articles I will expand each of the layers. This one is dedicated to the Search and Analysis component.
Before we dig into the component content, I would like to bring some background about its significance.
An important introduction to Social Network Analysis
Last week, I had a meeting with a college headmaster to figure it out if there was alignment between me and the headmaster’s expectations and values regarding how students will be prepared for the forthcoming decades, taking into consideration the shift we are facing regarding work patterns, information overload and technology disruption.
The institution is catholic oriented and have strong roots with the Catholic Church. Let me say that I do not consider myself catholic as by the book definition, but probably I’m more catholic that others that go to the church every day and don’t have ethics and values. This means I did not choose to evaluate the institution because it is linked with my religious beliefs, but because they are the best institution according to the evaluation program that was created by the Portuguese Government some years ago.
During the interaction with the headmaster (a religious person), we talked about two vectors I introduced into the conversation: values and student preparation for the forthcoming decades (how we prepare people to interpret and act on information and how they improve reasoning in the knowledge era). When the headmaster was talking about values, introduced an amazing characteristic from the human being point of view (sorry by the religious background I’m putting into the discussion but I consider that it’s worth for the sake of clarification about social network analysis).
God created humans as a single and unique entity. There are no equal human beings (even perfect twins) and God created animals and all the other living organisms differently that belong to a system (let us call planet earth that belongs to other system called the universe) made by diversity in constant balance and adaptation.
This point of view opens and reinforces the main characteristic that we humans who belong to families, communities, organizations, arrangements that are part of a super system called the universe whose foundations rely on the top of diversity and complexity, not on standardization. Somehow, we keep pushing in into an ordered regime because it is much simpler to understand concepts, interactions and our own existence in an controlled manner rather than in a complex one.
The world is complex and we cannot change that as much we would like to
Ashby’s law teaches us that any system must match the complexity of its elements in an actively and adaptive way to survive and prosper.
In addition, Ashby pointed out other important conclusion: any attempt to limit part of the variety (because it is considered noise by the humans) that constitutes the system will lead that the system will lose the capacity to adapt and lead into implosion. This reflects in the way some business processes cannot respond to exception handling, because the misleading adaptation consists into fighting against the process model rather than adapt to changing executing conditions. If we consider a different organization layer like strategy management, think when external signs are ignored that can lead the organization to bankruptcy or financial loss.
In the social era we are being misleading about what is Social Network Analysis, one of the reasons it is about the semantics, the meaning of Social, broadly understood connected people, but a Social Network is much more than that. In very general terms a Social Network can be described as a graph whose nodes (vertices) identify the elements of the system. The set of connecting links (edges) represents the presence of a relation or interaction among these elements. With such a high level of generality it is easy to perceive that a wide array of systems can be approached within the framework of network theory .
Social Networks can be made of Organizational Units, Business Units, Roles and Functions, Individuals, Data, Technology consumption (what part of the IT solution is used), Technology interaction (how IT solutions communicate), Business Processes, Traffic, Biological, Physics (these last two categories lend so much of its properties to business analysis) etc.
All the networks are self organizing systems, but there are important patterns that can be identified anywhere from the self organization, despite randomness, patterns are critical for humans to understand how data can be transformed into information, that ultimately is transformed into knowledge used to understand the behavior of such networks (see note below).
Self-organization refers to the fact that a system’s structure or organization appears without explicit control or constraints from outside the system. In other words, the organization is intrinsic to the self-organizing system and results from internal constraints or mechanisms, due to local interactions between its components  (that can be put on top of a business process). These interactions are often indirect thanks to the environment. The system dynamics modifies also its environment, and the modifications of the external environment influence in turn the system, but without disturbing the internal mechanisms leading to organization  (think for example social interaction with customers that change the course of the business process, or events during product research and development that makes to alter the characteristics and features). The system evolves dynamically either in time or space, it can maintain a stable form or can show transient phenomena. In fact, from these interactions, emergent properties appear transcending the properties of all the individual sub-units of the system  (and these emergent properties are the ones than be understood using a combined set of discovering techniques like process mining, social network analysis and data mining).
I tend to agree that with argument that looking for patterns into a complex landscape is a waste of time for the reason that into complex domains any attempt to take a snapshot is a distorted version of the reality. Nevertheless, the objective of patterns discovery and understanding is not to predict behavior but to infer trends or in Jason Silva’s words “to understand is to perceive patterns” http://vimeo.com/34182381 .
The objective of Social Network Analysis is not to predict outcomes, but to understand, to construct knowledge around emergence self-organization and adaptation in scenarios like for example decision making or distributed systems that are becoming real enterprise challenges as business complexity and interactions grow exponentially.
Huge amount of data is being recorded today (see image bellow) that allow us to make discovery and analysis of complex interactions. The argument that does exist and it cannot be done only fits in a category like airport security information that typically relies on paper.
The Internet of Things – new infographics – Source: Bosch
On part two, I will explore techniques to analyze social networks.
On Fastcompany’s article: “IBM’s Watson Is Learning Its Way To Saving Lives” is said that “Watson is poised to change the way human beings make decisions about medicine, finance, and work” […] “They believed Watson could help doctors make diagnoses and, even more important, select treatments”. I argue that IT can help humans to process and show data to help humans to make better decisions. Last weekend, a family member stood at a hospital during a day making analysis on what could have been a heart attack. Diagnosis were automatic: they make a 1 minute electrocardiogram (considered insufficient by experts) combined among others with measurement of troponin levels (diagnostic marker for various heart disorders). The results found correlation between the results and the family member was told a cardiologist should immediately see him. When the cardiologist looked to the results he said that there was no correlation at all, the results of the electrocardiogram were insufficient and the troponin level was 1/100 of the danger threshold and was unlikely to raise suddenly. In the end the diagnostic was wrong and the cause of sickness was nervous system. This evidence like many others should make us think as Einstein said: “Information is not knowledge, the only source of knowledge is experience”; I would add information cannot be stored.
 Preliminaries and Basic Definitions in Network Theory – Guido Caldarelli and Alessandro Vespignani – Large Scale Structure and Dynamics of Complex Networks: From Information Technology to Finance and Natural Science – World Scientific Publishing Company – ISBN 978-9812706645
 Self-Organisation: Paradigms and Applications – Giovanna Di Marzo Serugendo, Noria Foukia, Salima Hassas, Anthony Karageorgos, Soraya Kouadri Mostéfaoui, Omer F. Rana, Mihaela Ulieru, Paul Valckenaers, and Chris Van Aart – Engineering Self-Organising Systems – Springer – ISBN – 3-540-21201-9
On a previous post called The three layers of social business I discussed the importance of understanding a social business as an ecosystem rather than focus only on the technology menu.
As the Social Business Community Group puts in the A CTO’s Guide to Social Business, a social business is:
A social business is an organization that applies social networking tools and culture to business roles, processes and outcomes. A social business enables people to engage productively in a business context through collaboration and interconnecting business activities with social content. The scope of a social business spans across internal organizational boundaries and can extend to partners and customers. A social business monitors and analyzes social data to discover new insights that, when acted on, can drive business advantage, for example faster problem solving, improved customer relations, predicting market opportunities, and improving processes both internal and external. A social business recognizes that people do business with people and optimizes how people interact to accomplish organizational goals.
What is social business alignment?
- Social activity is integrated in business processes across and is supported by social technology;
- Processes need to handle with social interaction at any point at any time, because the customer is driving the process, not the company. A Process that it’s designed on predefined manner will fail to cope with dynamics. Processes must be designed to spark others from the “middle of nowhere” rather than have predefined touch points. A customer maybe dealing with a complain and wants at the same time be informed about invoice settling. If you have difficulty to deal with this, one of the solutions for process design is a business rule based approach where processes focus on what need to be done, describing the available activities that can be performed at a process stage and the rules sit on top not allowing the process to deviate;
- It’s an ecosystem;
- It must have the right social network configuration (process bandwidth should reflect the knowledge dimensions that should support the outcomes customers are willing to be achieved);
- It must have executive commitment and participation (not the sponsorship, actually is the executives putting their hands on the tools as I’ve been told).
2. The platform:
The idea of the platform bellow was developed based on a previous work done by the W3C’s Social Web Headlights Task Force later adopted by the Social Business Community Group I belong , but it was kept in the closet for a while, because the target of these group is to foster standards development based on available technology.
There is no common definition for a social platform. Most of the community work around it focus too much on the technology the platform provides rather on the semantics or meaning of such platform is.
A social platform can be understood as the capability provided to an organization to deploy and manage onto an infrastructure artifacts into the layers that constitutes the platform.
The layers reflect the internal and external social interactions an organization executes regarding the organization environment it belongs and evolve over time. Those interactions that constitute the social practice are driven by technology that best supports the nature of work executed by the people.
The social platform is constituted by three main blocks as bellow illustration and it’s technically agnostic:
- About the Human: Who you are, how you identify yourself and what you pretend to be, the person’s social graph.
- Human Interactions: What you do. How do you express. How you engage. How do you react. Where you belong. What work you execute.
- Search and Analytics: Search for knowledge, gather feedback, get trends, spot patterns, sentiments, learn.
About the human is constituted by:
- Identity: Unique identification attributes about the human.
- Profile: What attributes about the human are available to identify him. Presence status (on-line / off-line …).
- Social Graph: Social network type, network type and network connections around particular domains (may exist different networks for different domains). The communication flow and how people are connected with. People can be connected through some kind of relationship (work with, partner of), but the most importantly is the information flow between the people, i.e. the working practice, information sharing, because is here where action occurs.
- Addressing: Contact details (e-mail, instant messaging … ).
- Reputation: Perceived evaluation taken by members of the social graph.
Human interactions are constituted by:
- Messaging: Conversations can be synchronous or asynchronous around a topic.
- Group dynamics: Communities of interest or practice, interacting around a particular domain.
- Collaboration: Work being carried towards a goal that must be achieved. Work can be structured or unstructured.
- Sharing: Accepting an object to be shared in order others can take action if they want to.
- Reactions: Expressing a feeling about an object , making an opinion or making an evaluation.
Search and analytics is constituted by:
- Search : Find information necessary to gather data to reason, to judge and execute tasks.
- Business Intelligence: Getting and explore data, finding trends, correlation helping people to do better decisions (if they know how to interpret it)
- Mining: Extract data and display it process oriented for business process analysis and improvement.
3. Technology is important but it’s not enough
The problem of focusing on the technology that makes social business happen is it creates a tunnel vision of making it a reality because technology alone does not provide the foundation of creating a full integrated into the organization value chain that includes all the stakeholders.
For example an airline can have a twitter account to broadcast announcements about events like strikes that do not allow the flights to operate properly and that is a plus, but it that twitter account it’s not able to catch important feedback about traveling issues and annoyances of the passengers and integrate that feedback into customer support what is the value of using twitter as a communication tool? By the way I will come back to this issue when I have time to seat and write about it, how UPS is mastering complain handling using social technologies. “Scooping” around it I will like to tell you that in the US, UPS is taking seriously how complains are handled unlike in Portugal where they don’t even let you make it until the next day I received a phone call regarding a complain I sent to the headquarters (strange, I thought I did a complain to the local office!). As you can see even inside of enterprises there is no common foundation what is a social business and most of the times managers are worried in choosing a proper tool to say they use it, is there, and it’s available but it’s not integrated on the value chain (this is a challenge to Enterprise Architects).
On April this year I wrote a post about one of the challenges that Process Mining is not addressing properly: Big data. In the last process mining task force meeting, resulted that one the biggest concerns was about the effort of making XES a “de facto” standard in order event logs used in process mining could be system interoperable.
Despite the fact is important to assure that data can be exchanged across multiple systems and they can be interpreted the same manner (contrary what happens with bpmn diagrams), I tend to think that process mining is loosing ground regarding the near future reality:
- Technology will be like electricity or if you prefer a commodity;
- Cybernetics principles will emerge (finally) because society and technology is backing humans able to observe, sense, act, learn and adapt. Once organizations are made from humans, and despite humans belong to some kind of organizational unit, they are not anymore animals on a tree branch and are part of social networks that constitute the enterprise where everything happens.
- Technology no longer shapes the way human perform. People do it. Change and adaptation encompasses clearly to think and find new business models. To think about innovation. If companies do not have humans capable to find access, understand and process information, how can companies evolve and survive?
Again what is the challenge of process mining?
Organizations live in a world where interdependence, self-organization and emergence are factors for agility, adaptability and flexibility plunged into networks. Software-based information systems go into a service oriented architecture direction and the same goes to Infrastructures where services are become structures available in networks. inspired into empirical studies of networked systems such as Internet, social networks, and biological networks, researchers have in recent years developed a variety of techniques and models to help us structurally understand or predict the behavior of these systems. Those findings are characterized by been supported on the “complex networks” concepts .
Last week I stumbled into a great find based on a conversation about creating an Adaptive Enterprise Architecture framework to support business processes that Process Sphere is sponsoring, in order to apply in real world implementations. Universidade do Minho is leading research in the field of understanding existing information systems can be characterized adopting the complex adaptive systems principles.
The approach is quite obvious (and at the same time so simple). Is about a black box (supplied by Palo Alto networks) connected to the enterprise network (the pipes where information flow, where today everything flows) and literally sucks all the information from the pipe to be analyzed and interpreted. With this approach its possible to understand Who interacts an with Whom interacts, What information is accessed and processed, What and When, interaction occurs, What are the information services requested and (in my point of view) particularly important evaluating how information systems can cope with social iteration and can keep the pace of adaptability inside of organizations (something I’m keen regarding other project about requirements engineering using process mining).
The innovation of the approach is based into:
- Analysis is carried based on complex network principles;
- Contrary of one of process mining principles, that the staring point is to select data to make the analysis in order to prevent “data collection paranoia”, this project collects and analyses ALL the available data and digs into the networks that were formed (each network have a different analysis dimension depending on the field of analysis). Layered.
On one hand the method approach to interpret data it’s arguable among the scientific community that the one here presented is inferior of others used by other researchers that develop process mining methods available in tools (researchers tend to think they are above God), thus I’m not going to involve in that kind of discussion (by the way this one comes from physics), on the other hand, what I like most is the design approach. Putting a box so suck all the data to be explored (into the company veins) what could be called inline real time process mining to deal with complexity and adaptability.
References:  Modeling Organizational Information System Architecture Using “Complex Networks” Concepts, José L.R. Sousa, Ricardo J. Machado, J.F.F. Mendes, 2012 Eighth International Conference on the Quality of Information and Communications Technology
Social interactions continue to attract conversations, because they are introducing shifts the way people access information, communicate and work. This shift did happen due deregulation of the financial markets in the 80′s, driven by development of technological infrastructures (telecommunication and information systems), combined with computer power capable of the high speed algorithms processing required to handle the complexity of financial transactions, not because millennium generation and others want it and are eager to be connected.
Every time a new concept in introduced in the business community hype is created and everybody wants to follow, copy and use it. Social business is one of the most discussed themes these days. Facebook bought Instagram and the .com bubble is bringing cream full of sugar to our lips (how loved the late 80′s!). If you want to start your social journey it can be useful take a peek to this social business book list posted by Dion Hinchcliffe. Or not.
It’s useless to start you social journey if your social structure is not aligned with the process bandwidth played. But the process bandwidth should reflect the knowledge dimensions that should support the outcomes customers are willing to be achieved.
How a star can kill your social efforts
Forget for now the book list. The first thing, as a manager you need to understand is the network type that exist inside of your company. A method to carry on this assessment can be found in this previous post. Process Mining can be one of the tools you can use to find out the type of social networks that exist in reality. Organizational charts, do not reflect the way people interact.
Discovering the types of networks that exist is the first step to carry on the assessment. you need to understand the communication flows patterns. An organization is the result of time-sharing social practices that work through flows. And flows (represented in social networks by arcs between nodes that represent the actors or process participants) are the activity sequence between participants. In order words you need to find the dominant social structure.
The assessment will show two important attributes:
- The nodes – the process participants. The way the network of nodes is highly or loosely coupled or of the roles of interaction and propagation involved.
- The way people are organized around knowledge type from Tacit to Explicit in different boundaries (inside the company and outside the company). Tacit knowledge is related with judgment, intuition, reasoning, in order words with unstructured / dynamic /adaptive / ad-hoc (I put all the possibilities in order not harm beliefs), annual/industry reports ; Explicit knowledge is related with procedures – structured processes, companies policies, industry culture.
Hence, without further explanation, it’s pretty clear that if your company plays more unstructured process instances and the discovered network is highly coupled around a hero or a star (decisions are centralized) knowledge will not be spreading and you have a very inflexible company.
Enterprise architecture is about alignment. Encompasses the entire enterprise. There is no meaning if you want to copy CISCO culture, providing autonomy, empowerment, social tools, whatever, if your network blocks flow communication.
John P Scott, points some basic network structures that you can use to carry the assessment. I will explore it regarding the consequences of knowledge flow and alignment regarding the process types that in theory are executed. For social networks discovery it’s necessary you define the discovery scope first (choose a process and start mining; in some organizations like healthcare providers, the “process” start when you are admitted in a hospital until you leave, thus mine for function). Other way to define the scope is mining the same process, comparing how social networks are structured across different countries or business units. This last one can be a important, as Isabel Ferreira, CEO of Best Bank said recently
One of the major challenges is to expect the same performance in different countries. We provide the same tools, the same goals to be achieved, still there are differences in performance. The differences come from the way people work and communicate together. A manager needs to understand what is wrong regarding how people are engaged and make adjustments. Business Intelligence will tell you nothing how people are connected, just shows you if things are right or wrong, because it’s not process oriented.
Management style shapes the network configuration and the outcomes. I’ve seen some high achievers informal networks capable to deliver top results.
- Star networks: Characterized by being strong central and weak distributed. These kind of networks are typical of structured processes. Every decision is approved and people play a well defined role and hierarchy is imposed as formal authority. People play the same activity one after the other and the very same result is achieved on every process instance.
- Star with multiple core networks: Characterized by being strong central and strong distributed. Here, someone is responsible to orchestrating others, that have their own links to achieve an outcome. Feedback is shared, but it’s “sent to the network star”. Relationships are maintained by authority like in start networks, but communication between peripheral members is maintained and it’s improved if peripheral members maintain a close connection.
- Multiple core networks: Characterized by being weak central and strong distributed. Typical of adaptive processes. As the process progress, resources join the quest to find a solution to achieve the outcome. Feedback is shared, but is not centralized. These networks are formed based on tacit knowledge and trust. Finding people inside big organizations with plenty and the right Tacit knowledge can be difficult, thus people will stick to the ones they are acquainted (this can be a challenge if we want to involve the right people but we don’t know where to find it); trust plays an important attribute. Trust is one attribute of social interaction foundation. Looking to a broader level, companies that do not deliver a “relationship based on trust” with it’s customers will be in trouble if they want to engage with them. Today this is impossible. Going back to people domain, trust is important, because the others believe you will deliver independently the circumstances that change on run time mode.
- Loosely coupled networks: Characterized by being weak central and weak distributed. You can find this kind of networks on emergency scenarios, or if you are analyzing a company of heroes (meaning people work on a “last minute basis”).
Looking to the above patterns, looking the way information flows you would be tempted to choose the Multiple Core network and forget the Start type, because will be related with poor performance. But that does not hold true.
Social networks must be aligned with the process type played (structured, adaptive to emergency). And the process type played require different knowledge forms. There is an extra challenge , when the end-to-end process is blended regarding type, I mean, part is structured, part is not. Discovering social networks of this process types can be done using Process Mining filters that can shows you how people connect across the different parts of the process played according the activity sequence that defines it’s nature.
The key point is to align the network type with the process type.
- Star networks: These kind of networks are useful, contrary of what you may think, but only on highly automated, repeated processes. People play it’s role alone and report only to other that is responsible for the work is being carried and aggregate and control all the information (for example a contact center coordinator). These networks are inappropriate to knowledge sharing and dissemination, are tailored to extract the maximum of human resources available to perform. Information is analyze by the star or the starts of the network to find best practices and optimize how the work is carried.
- Star with multiple core networks: These kind of networks are useful, contrary of what you may think, but only on highly automated, repeated processes. People play it’s role alone and report only to other that is responsible for the work is being carried and aggregate and control all the information (for example a contact center coordinator). These networks are inappropriate to knowledge sharing and dissemination, are tailored to extract the maximum of human resources available to perform. Information is analyzed by the star or the starts of the network to find best practices and optimize how the work is carried.
- Multiple core networks: This is domain of knowledge intensive exchange. This is where complexity and unpredictability plays a role. Adaptation occurs from the feedback loops, and decisions are made according people expertize and experience. This is where new alternatives are explored to reach an outcome. Some will turn to be patterns (solutions) other will transform to best practices and will be lately automated on a predefined manner. On this kind of networks it can occur performance lags when network is formed if people are not acquainted (makes me remember my role in W3C and WFMC groups I’m working with) or due knowledge leveling (everyone knows the concepts meaning).
- Loosely coupled networks These networks are found in Emergency or Chaotic process types. Forget the Red books and Emergency plans. Under these circumstances people act first, measure the consequence and adjust until it’s possible to resume under more controlled or predictable circumstances, that can be played according the knowledge intensity (more intense adaptive process type, less intense structured). When the process resumes to new process type, it’s expected a shift in the network structure.
The wrong way to Hollywood:
Before you start your social journey, because you feel you are not engaged with your customers, you do not understand what they are talking about you, your process architecture is not designed to handle complains from Twitter, or internally you rely in clutter e-mail, point to point communication, or the enterprise content system does not allow project team members to reuse, learn, with other projects outcomes and your are anxious to adopt a social stack, before doing it, analyze and align your social network structures. If you are a manager and the dominant type a Start network and you need your knowledge flowing, not centralized, social technology is useless.
As most of sociologists write, consultants like to draw concepts in matrix graphs like the one above. I concur with this criticism regarding it does not show the dynamics of knowledge shifts that naturally occur inside organizations, because company mission changes or because naturally business processes do not belong to a single type, but are blended.
If you are interested how you should align network structure to the process bandwidth your company play, join me at Business Process Management Conference Europe 2012. A preview of what is going to be presented can be learned also in the webinars hosted by BP LOGIX.
Polanyi, M. :The tacit dimension. New york Doubleday, ISBN-13: 978-0385069885
March, J. G. : Exploration and exploitation in organizational learning. Organization Science, 2, 71-87
Nonaka, I: A dynamic theory of organizational knowledge creation. Organizational science, 5 pages 14-37
Scott, John P : Social Network Analysis: A Handbook, Sage Publications Ltd, ISBN-13: 978-0761963394
How Knowledge Workers Get Things Done
BPM Conference Portugal
Process Mining Camp 2013
BPM on Adaptation Change and Innovation
- #Chaos & disorder cognitive-edge.com/blog/entry/600… Mapping knowledge assets. #BPM #ACM via @CognitiveEdge 11 hours ago
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