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Enterprise Architectures for Artificial Intelligence (III)

Taxonomies of Artificial Intelligence

There are at least five ways to position AI in the enterprise landscape:

1. By processing method: batch, micro batch and real time
2. By algorithm type: pattern recognition, clustering, associations, scoring, predictive, classification, text, speech and image mining, …
3. By data type: high vs low dimensionality, graph data, self-describing data vs structured schema data, machine vs human sourced data, mediated data registration vs direct data registration,…
4. By data behaviour: volatile vs stable data values, long vs data persistency,
5. By analytics goals and or business process: churn prevention, prospect qualification, complex evaluations of loan applications, CVs, customer feedback, basket analysis, next best action proposals, fraud detection …

The enterprise architect will choose the relevant combinations between these taxonomies to produce a coherent end-to-end vision on the architecture. A possible selection criterion is the governance model used in the organisation. In a business monopoly analytics goals will be leading and combined with algorithm type. In an  IT monopoly processing methods combined with data behaviour is the most probable direction and in a duopoly, well,… that depends.

Let’s do an exercise and suppose this is the outcome of a duopoly governance model: combining the processing method with the algorithm type to indicate which processing method is most suited for the chosen algorithm type. Using this schema may help to manage expectations between the business and the IT people better.

	Batch	Micro batch	Real time
pattern recognition	Ideal method for large data sets	Suited for simple patterns	Only as a binary in/out of pattern decision which implies a large (batch) training set
clustering	Ideal method for large data sets	Suited for simple clustering criteria	Only as Y or N adherence to an existing cluster which implies a large (batch) training set
associations	Ideal method	Hardly possible	impossible
scoring	Develop a base line	Adjust the base line	Score against the base line
predictive	Develop a base line	Adjust the base line	Match with the trend
classification	Train the dataset	Classify new data	Simple classification
text mining	Train the dataset	Reveal polarity, topics, etc…	Deliver alerts
speech mining	Train the dataset	Reveal polarity, topics, etc…	Deliver alerts
Image & video mining	Train the dataset	Classify images	Deliver alerts

From this crosstab, it becomes possible to position the concrete algorithms, the data sets and their life cycle management, the ingestion volumes, timing and the technology to deliver on the various promises made.

Other methods will give you paths to the same end result: a coherent and methodical inventory of the landscape, linking business processes to AI and data mining initiatives and routines as well as the data and the applications to deliver the goods. Based on a gap analysis, the enterprise architect can develop a roadmap that communicates with all parties concerned.

Enterprise Architectures for Artificial Intelligence (II)

A generic model for primary processes

Every organisation is unique but most organisations share some basic principles in the way they operate. Business processes have some form (between 5 and 100%) of support by online transaction systems (OLTP). Business drivers like consumer demand, government regulations, special interest groups, technological evolutions, availability of raw materials and labour and many others influence the business processes intended to deliver a product or service that meets market demand within a set of constraints. These constraints can range from enforcing regulatory bodies to voluntary self-regulation and measures inspired by public relations objectives.

This is a high level approach of how AI can support business processes

High level generic architecture

Business drivers are at the basis of business processes to realise certain business goals and delivering products for an internal or external customer.  These processes are supported by applications, the so-called online transaction processing (OLTP) systems.

Business process owners formulate an a priori scoring model that is constantly adapted by both microscopic transaction data as well as historic trend data from the data warehouse (DWH). Both data sources can blend into decision support data, suited for sharply defined data requirements as well as vague assumptions about their value for decision making.  The decisions at hand can be either microscopic or macroscopic. 

Introducing AI in the business processes

As an architect one of the first decisions to make is whether and when AI becomes relevant enough to become part of routine business processes. There are many AI initiatives in organisations but the majority is still in R & D mode or –at best- in project mode.  It takes special skills to determine when the transition to routine process management can provide some form of sustainable added value.

I am not sure if these skills are all determined and present in the body of knowledge of architects but here are some proposals for the ideal set of competences.

• A special form of requirements management which you can only master if the added value as well as the pitfalls of AI in business processes are thoroughly understood,
• As a consequence, the ability to produce use cases for the technology,
• Master the various taxonomies to position AI in a correct way to make sure you obtain maximum value from the technology (more on this in a next post),
• Have clear insights in the lifecycle management of the various analytical solutions in terms of data persistency, tuning of the algorithm and translation into appropriate action(s).

In the next post, I will elaborate a bit more on the various taxonomies to position AI in the organisation. 

Enterprise Architectures for Artificial Intelligence (I)

In the past three decades, I have seen artificial intelligence (AI) coming and going a couple of times. From studying MYCIN via speech technology in Flanders Language Valley to today’s machine learning and heuristics as used by Textgain from Antwerp University, the technology is here to stay this time.

Why? Because the cost of using AI has fallen dramatically not just in terms of hard and software but also in terms of acquiring the necessary knowledge to master the discipline.

Yet, most of the AI initiatives are still very much in the R&D phase or are used in limited scope. But here and there, e.g. in big (online) retail and telecommunications, AI is gaining traction on enterprise level.  And through APIs, open data and other initiatives, AI will become available for smaller organisations in the near future.

To make sure this effort has a maximum chance of success, CIOs need to embed this technology in an enterprise architecture covering all aspects: motivations, objectives, requirements and constraints, business processes, applications and data.

Being fully aware that I am trodding on uncharted territory, this article is –for now- my state of the art.

Introducing AI in the capability map

AI will enhance our capabilities in all areas of Treacy & Wiersema’s model, probably in a certain order. First comes operational excellence as processes and procedures are easier to describe, measure and monitor. Customer intimacy is the next frontier as the existing discipline of customer analytics lays the foundation for smarter interactions with customers and prospects.

The toughest challenge is in the realm of product leadership. This is an area where creativity is key to success. There is an approximation of creativity using what I call “property exploration” where a dimensional model of all possible properties of a product, a service, a marketing or production plan are mapped and an automatic cartesian product of all levels or degrees of each property with all the other properties is evaluated for cost and effectiveness. Sales pitch: if you want more information about this approach, contact us.

Capabilities where state of the art AI can play a significant role

Examples of capabilities where AI can play a defining role. Some of these capabilities are already well supported, to name a few: inventory management (automatic replenishment and dynamic storage), cycle time management (optimising man-machine interactions), quality management (visual inspection systems), churn management (churn prediction and avoidance in CRM systems), yield management (price, customer loyalty, revenue and capacity optimisation) and talent management (mining competences from CVs).

Areas where AI is coming of age: loyalty management and competitive intelligence, R & D management and product development.

In the next post I will discuss a generic architecture for AI in support of primary processes; Stay tuned and… share your insights on this topic!

Relevance Lost 2.0

When Robert Kaplan and Thomas Johnson wrote about the fall of management accounting systems and pleaded for new perspectives and approaches to strategic process control they wrote a most relevant statement that still stands today. But as organisations are implementing performance measurement systems as applications of their business intelligence infrastructure, news risks of losing the most relevant part of strategic management arise. There is a clear need for a new, extended approach to the balanced scorecard (BSC). If you wonder what this may be, then read more.

In this article I describe the generic strategy process, compare this with the performance management process, how it is implemented in some organisations and analyze the aspects of this process related to the organization’s leadership style and thus the consequences for the balanced scorecard’s effectiveness.

The Strategy Process: Formation and Formulation

Every organisation has its own way of forming and formulating a strategy. It is in the organizational DNA: the way strategic objectives are grounded on a clear problem statement, SWOT analysis, competitive analysis, etc… and evaluated, proper to that same DNA.

Fig 1. The Strategy Process The strategic objectives entail the position of the company for mid- and short term, wanted behavior from clients, associates and partners. These objectives are then dissected, evaluated, scored and appreciated according to the organization’s values and beliefs, the organizational culture and past experience. 

The last phase is the decision phase where the objectives are translated into concrete actions and measurable products and outcomes of these actions.

As the illustration shows, the strategy formation process is usually done in four process steps:

• definition, 
• dissection, 
• evaluation and 
• decision

In the definition process, the strategic problems and opportunities are described and expressed in statements like: “We are not well positioned in the high end market”. Input for this process step is SWOT analysis, as well as analysis of the competition and the customer base. 
In the dissection process, expressions like “We are not well positioned…” are set in context and translated into critical success factors, e.g. “In order to improve our position in the high end market we need to upgrade our image, educate the sales force, identify more high end customers.”
The eva luation process is mainly concerned with prioritizing the dissected elements and looking for causal relationships between these elements to prepare a cohesive and consistent strategic plan which can be communicated to all parties concerned.
Finally in the decision process, the prioritized and feasible targets and ways to achieve these targets with global action plans are chosen. Some targets are based on decisions with tangible and measurable results and others are based on long term decisions with immaterial and almost immeasurable outcomes. 
The following decision points are ranked from very concrete and “hard” targets to more “soft” and less quantifiable decisions:

• which critical performance indicators will receive priority in the action plans and budget allocation,
• which actions are needed in the market place,
• which organizational behavior needs adjusting
• what needs to be improved in the organization’s culture

In the strategy formulation process steps, communication exercises will adjust these elements to match them with the various target groups: associates, clients, suppliers, shareholders, government officials, press, etc…

The Degrees of Collaboration in the Strategy Process

If we imagine a continuum in leadership styles, ranging from autocratic to democratic leadership, the four strategy formation process steps will be subject to shared inputs, transformation and outputs on a scale of zero to hundred percent.

In an autocratic leadership all four process steps are in the hands of the leader. Only the leader decides what is important in the environmental scan, what the objectives are, how the actions  are prioritized. Some autocratic leaders have problems formulating the strategic plan as they still hold up the adage “knowledge is power”. What they gain on control may get lost in the execution phase when their subordinates try to interpret their ambiguous communication.

Long time ago, I studied the biographies of dictators (which names I won’t mention because they deserve to be forgotten) and it struck me that often they communicated very vaguely about their strategic vision, priorities, objectives and the way to accomplish these objectives. Zealous and ambitious subordinates would then translate these cryptic messages into complete (and often horrific) action plans which would then be meticulously and ruthlessly executed. After which the dictator either rewarded the zealot or had him sent in exile because he became too popular or was a liability for the regime to the outside world.  Nevertheless, autocratic leaders can be highly successful in process industries, retail, service organisations and this leadership style emerges everywhere there is a crisis and fast response times are more important than a well pondered decision making process, balancing all market factors, interests and wishes in the organisation.

 In the democratic leadership all four process steps may be in the hands of the entire team. Lengthy discussion and negotiation may require a lot of resources but the upside is that everyone in the organisation is on the same page and the execution phase has less need for control and clear instructions as the organisation members act in a more autonomous way, responding faster to changes on the terrain. Organisations of professionals prefer democratic leadership as knowledge and competence are far more important than rank and power and the status that go with it.

Finally in mixed forms, the definition process may be initiated by the strategic apex, shared with the ranks and business analysts may be called in to dissect the statements into  manageable chunks.

The evaluation and the decision process, depending on the level of democratic leadership, may be done by the leader, a management team or a management team extended with staff members and analysts.

Today, as organisations become flatter and more democratic leadership styles are proper to new industries, there is a need for faster feedback loops to combine the advantages of autocratic leadership with the responsiveness of democratic organisations.

The Performance Management Process

The strategy process, seen from a performance management perspective, is a machine-like approach to define, monitor and manage the actions as defined in the strategic plan.

Let’s see how the strategy process is broken down into the performance management process. The performance management process breaks down the strategy formation process into smaller chunks to decompose the formation (definition, dissection, evaluation and decision) into nine steps.

This is a top down exercise:

·        Analyze the situation (SWOT, competition,…) (Definition Process)

·        Determine the objectives after the analysis (Definition Process)

·        Define the critical success factors (CSF) (Definition & Dissection Process)

·        Derive the critical performance indicators (CPI) from these CSFs (Definition & Dissection Process)

·        Mapping the CPIs on the organizational units down to the individual associate (Dissection & Evaluation Phase)

·        Adapting the HRM policies to these mappings (if trade unions allow, of course) (Evaluation Process)

·        monitor, manage and readjust the CPIs (Execution process)

·        monitor, manage and readjust the CSFs (Execution process)

·        Adapt the objectives to the new SWOT results (Execution process)

Remark how implicit the decision process is embedded in the dissection and evaluation process steps of the performance management approach.

Strategy automation?

In the past ten years I have worked on IT-support for balanced scorecards (BSC) in a university, a bank, an insurance company and a manufacturing company. In all of these cases, a poignant conclusion was unavoidable: “If all you use is a hammer, everything starts looking like a nail”. The ICT tool became a substitute for the strategy process and forced a freeze on the organisation. Let me explain this.

The BSC was used as an instrument to implement a top down strategic governance of the organisation. The strategy decomposition as described above is then modeled in the ICT tool creating links and correlations between the various CSFs and CPIs. Identifying these cause and effect chains is not a trivial matter. If sales go south, all sorts of explanations may present themselves to the organisation. E.g.: Are lower sales due to:

·        … lower consumer confidence?

·        … a competitive move?

·        … a government announcement?

·        … simple seasonality or a gradual shift in seasonality?

·        … the weather?

·        … all of the above?

Or can the sales slump be explained by a factor we can influence like the number of sales training hours received by the sales reps? But then the question arises if there is a correlation between the amount and quality of the training received and employee satisfaction? Or is it the other way around:  because our employees are not very satisfied with their job, they respond poorly to the training received[i]?

But that is not all. As we all know, strategic management is about adapting to the environment. If the ICT tool does not capture  the environmental change either bottom up or top down, then what? There is also another side of the coin: if the strategic decomposition leads to individual targets, personal development plans and other HRM tools how does this affect the flexibility of the organisation to adapt to change?

People act accordingly to the incentives from management: either they integrate the CPIs in their work planning and their approach to the job or they look for ways to beat the system. I remember sales people holding back order forms for a yearly publication to “smoothen” the CPI measures of bookings per month since management did not take seasonality into account when the performance indicator was defined.

Strategy Dialectics Are the Way Forward

It is clear that the latter is unwanted behavior but those who conform with the system should be rewarded, shouldn’t they?

The answer is an ambiguous “Yes and No”. “Yes” if their response, steered and governed by the performance indicator, is in sync with customer demand. And “No” if this is not the case. Needless to add that any strategy which is not sanctioned by your customers is not worth the paper it is written on.

But how are the designer, the monitor and the manager of the balanced scorecard to know this? Henry Mintzberg (1994)[ii] makes the distinction between intended and emergent strategies and the way I see it and experienced it, the balanced scorecard is an almost perfect tool for managing intended strategies. It uses a negative feedback loop, just like a thermostat. And just like a thermostat it sometimes oversees the efforts needed to keep everybody in line with the intended strategy. So people who don’t meet their targets are stimulated to do so or they are made redundant if they are not likely to comply with the desired behavior. But as John Lennon so rightly said “life is what happens while you are making other plans”. Management may have misinterpreted the signals from the environment or changes in the market may be unnoticed by management. In that case,  emergent strategies may provide the answers to these situations as there is some form of “wisdom of the crowds” in the collective response from front office workers and anyone else who is in contact with customers, competitors, prospects, suppliers, researchers and government officials, to name a few. To capture these emergent strategies, the system needs to provide positive feedback loops to reinforce unplanned but successful behavior, even when it is non compliant with the intended strategy. In other words, if top management makes a mistake, it will get noticed in three to five years but if the front office worker makes a mistake, the organisation has an acute problem.

This calls for a special form of management, allowing dissidence in the ranks and considering experimenters and contrarians as assets instead of a liability. “Is this May 1968 all over again, when it was forbidden to forbid?”, I hear you say. No, thanks.

But imagine an organisation form where the exchange between the hierarchy and the ranks is formalized, open, unbiased and where everyone’s fact findings and opinions are accessible to everyone for discussion, refining and leading to decisions and actions.

Imagine a special form of knowledge management which goes further than a glorified chat room and text mining.

Imagine a system supporting both bottom up and top down strategy processes, using the collective wisdom of the entire organisation. Technology may be able to design and build such a system but if management is not prepared to adapt its ways of developing, forming and formulating strategies then the developers needn’t bother.

Knowledge Management and Performance Measurement Systems in Modern Organisations

Remember the initial point I was making: intended strategy is only a partial explanation of the realized strategy because emergent or grassroots strategies contribute to-or reduce- the results of the intended strategy. Since no entrepreneur or manager likes to be only partially in control, we need a new approach to the balanced scorecard implementation. Maybe that won’t be enough, maybe we need to extend the scorecard’s toolset.

What if the exchange process were more important than the results of it?

What if the true outcome of the dialectic strategy process were -other than a plan with measurable results:

·        enhanced motivation because people see the context, the bigger picture and have  contributed to it,

·        a shared vision and sense of direction that enhances group cohesion,

·        a higher level of entropy, turning each individual into autonomous decision making entities without the usual chaotic side effects,

·        increased responsiveness to changing conditions or unexpected phenomena in the market?

  

What if the strategy process became a strategy dialogue?

What if the system could capture the dialogues between the workers and:

•                 middle- and top management,

•                 the customers,

•                 the suppliers,

•                 consultants,

•                 academics,

•                 opinion leaders,

•                 government officials,

•                 the data warehouse,

•                 the external information sources?

What if this dialogue were supported by a tool requiring almost no extra effort from the organisation?

Let’s examine the actions people perform in an office which are –often without knowing- valuable strategic information bits and are already captured partly or wholly by the existing systems.

Searches on the Intra- and Internet,

Consulting information providers ranging from Wikipedia to academic and government sources,

Sending and receiving e-mails,

Creating and reading documents like meeting notes, documentation, process descriptions, …

Handling customer complaints

Dunning customers,

Online and offline meetings, chats,

Analysis and decision making,

etc…

All these activities leave traces in some or another information system. What if you could combine the most relevant words and constructs into input for your strategic plan, supported by a balanced scorecard approach but avoiding a rigid approach to the strategic process management? Let me have a go at specifying such a system and check if the technology is already available.

Performance Measurement Systems 2.0., a Functional Specification

The short description of this system is: ”A Collaborative Strategy Process Manager”   The architectural view is visualized in the schema below.

Fig. 2. The Core Architecture of a Collaborative Strategy Process Manager The architectural picture consists of three interconnected pillars: strategy, individual development and knowledge support. For simplicity reasons we leave aspects like servers, APIs and user interfaces out of the schema. Only the relevant functional blocks are listed. Remark that the planning and execution of the strategy is not in scope. Tools like ERP and CRM can provide the necessary support for that part.

The Organizational Strategy Management Process: this is basically the support for the balanced scorecard with a link to the personal development plans of the people needed to execute the strategy. We refer to vendors like QPR, SAS, and others to discover the features of a balanced scorecard software. But the link to personal development plans (PDP) needs to be established. Imagine this PDP as a database with relevant and “nice to have” competence development plans which are maintained during appraisal and evaluation interviews. If the HRM application can make the link with salary scales, a proper analysis can match the desired competences with the future wage cost trend.

The Individual Development Support: this is a personal balanced scorecard where the interconnections between interests, competences, knowledge and the track record inside and outside the organisation are managed. Imagine a kind of personal LinkedIn with extra depth in the competence area. Instead of generic labels like “marketing” one would find hierarchies like “Marketing > Market Research>Qualitative Market Research>Focus Groups>Brand Experience”

The Knowledge Support System: this pillar is not readily available of the shelve, but some components are.

The first block Search Engine Logs and Ratings bundles the information search behavior, the rating of the results but also the ratings of colleagues search results, and all other communication and processed information. It also includes ratings for decisions to be made by a group or an individual be it multicriteria analysis, simple voting, rule based decision making or more complex algorithms like ELECTRE. Bundling the information search and decision behavior can yield interesting results for the knowledge management team answering questions like “What information did he/she (or didn’t!) look for before making a decision?”

The Object Database is the engine behind the object aware user interface, suggesting hyperlinks whenever users integrate (potential) knowledge objects like information sources, notions, definitions, persons, etc… in their communication. This forces users to be clear about what they communicate and to what ontologies[i] their concepts relate to. These objects, ready for the object aware user interface are structured and edited by a knowledge manager or by the group, depending on the configuration which supports both autocratic and democratic environments. But the object database will also act as a repository for unstructured data which can then be presented to the group or the knowledge manager by “emerging publishers”.

The Object Database also disposes of easy configurable agents which respond to events or trigger events themselves, e.g. “Present the weekly list of most used ontologies”.

The Knowledge Modeling System is where ontologies, learning blocks and documentation blocks are created and managed. These learning blocks and documentation blocks are complete sentences or groups of sentences whether or not combined with illustrations to create the basic material for documentation like ISO process descriptions and procedures, help files and learning material for distance learning or learning on the job.

Finally,  the E-Learning System is where the previous material is used in learning paths, documentation maps and presented in a presentation layer which can be simple text and image, sound and/or video. The material can be used on purpose or pop up spontaneously whenever users struggle with knowledge gaps.

The three connections: the first connection is between the organizational strategy management and individual development tools. With this link, important questions can be answered and reality checks become possible.  A sample of these questions and checks:

                     •                 “Do we have the competences in house to deliver the desired actions?”

•                 “How big is the knowledge gap we need to close”

•                 “Where are biggest obstacles for change management?“

•                 “What unused competences suggest opportunities for new strategic directions?”

The second connection, between individual development and knowledge support tools makes knowledge management more manageable by delivering information to questions like:

• “What knowledge objects are most used by individuals, groups, teams, divisions,… ?”
• “When and where does who contribute to the development or the extension of knowledge objects?”
• “What e-courses have been successfully taken by whom?”

The third connection, between the strategy management support and the knowledge support challenges assumptions and probes for answers to questions like:

·        “Do we have the necessary capacity for the personal development plans?”
·        “Have we made the CSFs and KPIs sufficiently operational for the workforce to understand, adopt and apply them?”
·        “What level of comprehension of the strategy matches with a certain level of compliance to the proposed KPIs?”

·        “What new information can influence adjustments to the initial strategy?“What new information can influence adjustments to the initial strategy?”

If the “What” and the “Why” are implemented properly, the “Where” and the “How” will become easier to manage in an adaptive way because management control 2.0. will increase self control with individuals and groups but leave enough room for new initiatives to respond better to consumer demand.

Fig. 3 The Strategy Execution Process As the illustration suggests, there are two major directions to take when executing a strategic plan: changing the rules of the game or the organisational behaviour in case the results are disappointing or optimize the existing, successful strategy.  The “how” to this “what” can be both shock therapy or an incremental “frog in the pot of tepid water” approach. ultimately it will lead to managing the organisational competences, be they individual or group competences. The “where” is in projects or in processes, i.e. in new ventures or in routine things people do in the organisation. The “why” is not in this picture as it is supported by the collaborative strategy process manager as described above.

Conclusion

Strategy management is a slightly more complex phenomenon than the cybernetic view some scholars and managers have. An organization is a living thing, the environment is something even the biggest organisations can’t control (unless they are in a socialist island republic). Therefore, adaptive strategy management is the way forward.

Strategy management 2.0. will be adaptive or it will become obsolete in a flattened society, where successful organisations in the new economy have exchanged the hierarchical, top down, cybernetic management paradigm for a customer centric, responsive and adaptive organisation where people are motivated, empowered and share a clear vision, a sense of purpose and understand the general  direction the organisation is heading. Only that way, these organisations can face the challenges of a mobile, fragmented and volatile generation Z and build a sustainable business.

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[i] I use the definition from Tom Gruber from Stanford University: “In the context of knowledge sharing, I use the term ontology to mean a specification of a conceptualization. That is, an ontology is a description (like a formal specification of a program) of the concepts and relationships that can exist for an agent or a community of agents. This definition is consistent with the usage of ontology as set-of-concept-definitions, but more general. And it is certainly a different sense of the word than its use in philosophy.” From: T. R. Gruber. “A translation approach to portable ontologies.” Knowledge Acquisition, 5(2):199-220, 1993

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[i] In many cases, this cause-effect identification process is a matter of preparing the strategy formulation phase which has the implicit message: “This is how we see things” or a misused word in the business jargon: the often overstated “paradigms”.

[ii] From: Mintzberg, Henry: “The Rise and Fall of Strategic Planning” pp. 24-27, The Free Press 1994.