Digitized Production Service Solutions

Some companies are literally in the business of engineering IT infrastructures and managing the exposure of the company operations to those infrastructures.

For them, ITSM is part of a strategy to protect the value of providing IT to the business operations.

But from the demand side of things, credible providers are increasingly non-proprietary to the company. Meanwhile, the production value of IT utilization simply outweighs the impact on the Providers of doing the providing.

For companies not operated directly to engineer IT infrastructures, services still align IT to usability. The concept of a service and the agreement that defines service availability remains instrumental to making IT a part of business capacity.

But business seeks to align services to productivity. The point is that productivity dictates the requirements of capacity — instead of capacity dictating the potential value of availability.

 

SERVICES VERSUS DEMAND

Actual demand for service is linked closely to production requirements.

The value of production is far more sensitive to (a.) exposure to complexity and (b.) unreconciled scheduling. From the demand-side point of view, the primary assumption is that engineering creates an environment in which there can be reliable standing conditions supporting the opportunity to deliberately generate desired real-time outcomes. But, the on-demand world is emerging under management as a compilation of innovation, mobility, A.I., predictive analytics, dev/ops, lean, virtualization, and broadband. Meanwhile, the influence of competition, economies and cultures now more frequently causes changes in requirements. Consequently, use of services must be more flexible.  This means that the specific pathways and requirements of production may not be predefined and may need to be detected and composed “on the fly” with easily tolerable risk. Systems must continually or even suddenly generate processing that is immediately available to business operators.

Production Services Digitization

 

MANAGEMENT FOR BUSINESS

Demand-based strategic management of the production environment can be viewed thematically.

The management themes put an explicit emphasis on recognizing systemic conditions that promote immediate and adequate throughput of technology power, at low risk of misalignment to work objectives. The key themes ( in gray below) address the throughput constraints of on-demand production including target outputs, adaptability, governance, optimization and standards. They expect that management, services and needs are always negotiated in production.

Production Services Digitization2

 

Solution Providers are expected to address the elements of the model and the alignment of the elements. The elements shown in the model (such as context, knowledge or presentation) are all independently variable. But this means that the components of a solution can change asynchronously, directly affecting the complexity and integrity of the overall production system.

Elemental variability also highlights the hypothetical case of implementing full production throughput on terms other than through a single-source provider. A provider’s components offer more or less elegance and coherence to the production, and from one component to another, different providers have different levels of achievement in that regard.

In turn, that highlights the true importance of current-state digitization in IT.

 

DIGITIZATION

Digitization primarily means two things: one, the difficulty of engineering functional objects is greatly reduced; and two, the practical access to any implemented functionality is greatly increased. Digitization gives the same benefit to multiple sources, making each of the sources more likely useful to a given customer.

As a result, business requirements, for rationally maximizing the utilization of automation technology to exploit information, can be more generically defined by the customer aside from particular sources.

Said differently, essential business-relevant information uses such as explanation, instruction, communication and recording can be more readily modeled with a simpler architectural level of logic. In turn, the implementation of that logic in action can proceed in a faster time frame and with more assurance of operational stability.

Production Services Digitization3

 

THROUGHPUT DESIGN GLOSSARY

The business version of the production throughput model applies strategic goals (productivity, provision, management) to the production conditions, not just to the production outputs. It also applies goals (convenient, dynamic, integrated) to the runtime experience of the production.

In that demand oriented framing, the model broadly solicits the pertinent elements of a desired production solution. For example, catalogs and  location-triggered alerts both address service awareness. Collaboration functions and publishing both address knowledge. Discovery and mapping both address surveillance. Rules address interpretation; versions address referencing; and user interfaces address workflow.

More of the logic: demand-based management views on systems involve solution features that are automated and integrated specifically to apply to supporting production’s enablement with IT.

  • Presentation: consistent recognition and display of symptomatic evidence
  • Interpretation: formulaic or heuristic semantics and analyses
  • Referencing: policies, standards and specifications
  • Surveillance: real-time detection and exploration of states

Those assignments are part of the model’s persistent logic, while allowing both current and future components to apply.


Strategic Support Now

The customary “holy trinity” of People/Process/Technology still holds its place in IT strategy, accounting for key elements of managed value. Meanwhile, IT innovation has dramatically emphasized the central position of the individual user, who arbitrates tools and information with unprecedented liberties and options. This newfound power even directly challenges “process” by more frequently injecting improvisation into user procedures with beneficial results.

Because of this shift from process to people, it is far more important strategically to understand and manage why people do what they do. With that understanding, it is more evident that strategic support is fundamentally proactive, and is logically definable from the user’s point of view.

 

Support as Proactive User Empowerment

The general mindset of a User has an underlying structure that gives Support the indications of what generates manageability of the user’s acts and decisions towards getting “value” from IT utilization. The User’s self-image, desire, technology and information are all aimed at practicality, impact, expectations and decisions in a consistent way. The consistency comes from the User’s instinctive need to combine competency and autonomy (opportunity) for driving justified performance (outcomes). Proactive support consistently focuses on the practicality, expectations, decisions and impacts. The long-term significance of the consistency is that it accommodates the increasing breadth and pace of changes in user practices, tools and information without needing support to be re-conceived itself. Implementations of support can adapt and adopt within the same formula for generating business value.


Assessing the Individual Contributor

The personnel management bookends – of Hiring and Performance Evaluation – have both long ago outstripped most people’s intuitive ability to “objectively” foresee specific comings and goings. To some extent, we expect that those two efforts will be pushed in one direction or another by relationships that pave the “inside tracks” to adequate visibility and preference. The complexity and brute force of recruiting, references, and resume robots each can create many different paths, but the average person being evaluated doesn’t know what the particular path is at the time without lots of “inside” help. There are just too many variables.

Why are some people hired or fired when they appear only comparable to others who are not? How do they get on the necessary track to be chosen or retained? Or how does the track change and run out from under them without their knowing it?

The approach used here to reach an answer began by looking to neutralize (or set aside) “relationships”, while cataloging characteristics frequently observed being used as “selection criteria”. The characteristics all pertain to a candidate individual. The problem of selection is framed as a cross-referencing of Position (the chance to do something) and Skill (the ability to do something).

The high-level abstraction of Position versus Skill has been chosen because of its simplicity and directness in pointing at Effectiveness. The framework argues that Effectiveness, whether projected or proven, is the single most important factor in both the decision to hire and the evaluation of performance. Effectiveness Assessment_Individual_green

Most conversations about the reason for selection or rejection will feature a vocabulary found within this framework of “characteristics”. For any given occasion of evaluation, the characteristics are the criteria, and some of the criteria are emphasized significantly more than others. The emphasis comes from whatever is driving the perceived need to modify the organization at the time. The emphasis determines how important it is that any particular characteristics are sufficient and beneficial. Part of the equation for a candidate, then, is to show alignment with the current emphasis.

A critical difference between the Position criteria and the Skill criteria is that Position can be circumstantial and simply mandated. Position is intentionally highly variable and can easily be the source of a sudden misalignment with the current presence and arrangements of Skill. Skill, on the other hand, must be acquired or cultivated for the Position if it is to be meaningful.

In this approach, assessing effectiveness relies on the same information regardless of whether the effort is prescriptive before the fact or descriptive after the fact. Emphasis on one criterion or another shifts from time to time, but all characteristics are tactically significant in a standing general way as potential contributors to be leveraged by the organization. The vocabulary of that leverage tends to name outcomes recognized as effectiveness.

Meanwhile, as we know, relationships can be decisive by funneling key information to individuals about impending conditions, priorities and preferences.

 


The Design of Services

We intuitively understand that services allow us to have or do things that we don’t make or perform for ourselves. In theory, the best case scenario is that available services are tightly aligned to both our desires and our expectations. That brings in a variety of stakeholders who can create, use, and assure things heading in the right direction. But expressing what is needed, and how, to achieve the best scenario is often too imprecise and confusing to adequately work out, complete, and sustain or remodel against current and future circumstances.

The Archestra framework of service design parameters is an evolving artifact. Shown here is the framework as of May 2015.

The framework is an instrument for consistently identifying variable factors by which a service is obtainable and evident across its varying states of relevance (what service is the “right” one) and worth (what is the “upside” of the service). A single service may be “identified” through a variety of descriptive points of view; the framework contains them within a logical system of cross-references. Note (again) that the whole framework is used to refer to any single given service.

Service Design Parameters 2015

Goals of the framework:

  • Simple, explicit overall perspective
  • Uniformly global and pragmatic
  • Equally synthetic and diagnostic
  • Based on observable practices and events

 

  • No logical redundancies or contradictions
  • No reliance on a specific industry, business, process or technology vocabulary
  • No need for synonyms

 

  • Completely neutral: devoid of marketing, sales and philosophy clutter
  • Entirely compatible with governance, risk and asset management
  • Agnostic to physical vs. virtual, and actual versus logical, service formats
  • The semantics work the same way across Blueprints, Inventories, CMDBs, Portfolios and Catalogs, which intentionally select and assert distinctive views

 

  • Recognizes any manageable variable that can change the service structure or service status
  • Assures that any instantiated variables (realized actuals) are fully contextualized
  • Assures that different variables are never mistaken for each other

 

  • Supports classic modeling by exposing the identification, selection, integration and coordination of instantiated variables.
  • Shows that construction and deconstruction follow the same pathway
  • Shows that absence-or-presence of service is a logical threshold in a defined context, thus enabling knowledge-driven systematic problem management, policy determination, and renovation/innovation

 


Systemic Governance

Like defense or offense, governance is a high-level orchestration of multiple concurrent activities, conducted to create an overall state – in this case, a state of assurance of stakeholder values. Governance provides an orientation to activities that, by executing them under known constraints, aligns their impacts cooperatively towards assurance. This framework guides the orchestration.

 

Systemic%20Governance[1]

 

The background notes for this framework are here on Slideshare.

[Framework builder courtesy eXie]


Performing Innovation Under Governance

For those who manage performance, governance appears to offer a layer of security for meeting performance targets. But the scope of governance’s concern naturally exceeds the scope of production performance, representing a need to protect opportunity above and beyond performance targets. Inappropriate performance management will hold back innovation unless governance is appropriately influential on production.

Performing%20Innovation%20Under%20Governance[1]

 

The notebook accompanying this table traces the influence on the production environment that governance brings, with regards to supporting innovation. Click here to access the notebook.

 


I.T. is Dead; Long Live I.T.

The End Of Disruption

We have had over 60 years of business-class production based on intelligent automation through computing. During that time, business continually drove the evolution of the technology environment and focused intently on being a technology supplier itself.

Now, we have a change of view.

Thanks to the pervasiveness of the diversity of the internet, the demand perspective, not the supply perspective, is the heart of the business view – and Technology Information, not Information Technology, is the heart of the demand perspective on intelligent automation.

In the next normal, when the Internet of Things  (IoT) is the default activity platform, we get the return of information services to the top of the discussion queue.

Information services will allow relief from the limitations of strategy based on fixed process, and will begin maturation of techniques needed in the new production ecology.

Even more to the point, the default business view of service is about service information, not about service technology.

Demand-orientation creates a different understanding of services for production, while it explains the logical posture of management against constant environmental change.

Disruption only occurs when there is an over-commitment to low agility. This discussion lays out the management adaptation to services in the complex environment of the IoT.

Open The End of Disruption_IT Is Dead

Synthetic Intelligence for Production


The Requirements Gap

Interpretation of Needs


The Tao of “New”

“New” changes. Newness doesn’t.

Back in April of 2007, Optimize Magazine ran an article by M.S. Krishnan titled Moving Beyond Alignment. Its summary: strategic business innovation requires a flexible infrastructure so that the company can utilize the business models needed to achieve goals. Thus IT governance and architecture must enable the enterprise to “synchronize with changes in the business environment”.

Meanwhile, scheduled for late 2010, the book from strategic technology architects Greg Suddreth and Whynde Melaragno called The Path to Real Business Transformation discusses “dynamic synchronization… a rigorous, business-case-driven collaboration between the business-process owners and their IT counterparts.” For this, the framework of problem-solving is what they call business architecture.

“Innovation” always has an aura that suggests the big moment of arrival of the new. But getting to utilize the new is the only way that value is derived from innovation, and utilization requires integration into, and synchronization of,  the operational scheme of things. This emphasis on synchronization firmly declares that the problem of follow-through on business strategy is fundamentally about coordinating the moving parts.

Anyone who has tried to manually shift gears in a moving vehicle knows that synchronization has two operator-controlled aspects: time spent in the gear, and timing of gear changes. In a competitive context, where time and timing are pre-planned and managed for variances and circumstantial adjustments, this plan is even seen as a strategy itself. The performance level of the plan’s execution, especially in complex or volatile environments, is then most often seen as “agility”. Achieving agility is, for that reason, a common business objective related to scoring business goals.

Suddreth and Melaragno further state that “business architecture” is developed through a process that defines and institutes long-term change within a framework of strategy (for example of goals, related positions and directions), planning (for example, of resources), and execution (for example, of services). They go on to point out that multiple business areas must be complementary in the context of solving a defined business problem.

To assure proper pursuit of that agreement, it becomes necessary to appreciate the difference between innovative business uses of IT versus business use of innovative IT.

  • In the former case, the emphasis is on the business-level understanding of how moving parts might be aligned in a new way.
  • In the latter, the point is to introduce moving parts that have a different set of characteristics and interactions than those typically tried before.

From the point of view of these authors, the former issue is a concern of business architecture; and the latter issue is a concern of IT architecture, in which (among other things) the business architecture is  “physicalized” according to Suddreth and Melaragno.

Given those points above, it would seem that the challenge is to prioritize business innovation, then leverage business architecture to identify and incorporate IT innovation that can be scheduled within IT architecture for a reasonable chance of sustained synchronization.

 


The Next Normal

The next normal arrives when a new system replaces the old system in both its role and its opportunity as the preferred one to use.

A “system” occurs when a set of interacting items routinely take on a certain group behavior:  each of a critical number of elements acts, both consistently and persistently, primarily through their interactions with each other.

The routine behavior (i.e. the form) of the system occurs when the system is in a state of dynamic equilibrium, not just static configuration.

When a routine behavior consistently takes the place of a predecessor, the newer routine becomes the next “normal”.

In the next normal, new interacting patterns among the system’s internal elements are both more sustainable and more preferable than are preceding patterns.

The next normal occurs when two things happen.

One: an alternative system’s effectiveness becomes statistically predominant over an older system’s effectiveness. The difference may occur by force (causality) or by choice (attraction), leading to its potential predominance.  Impacts are the outcomes of interactions. Impacts are identified by types, not by levels. They can be forces, states, or objects. Effectiveness is the influence of the impacts.

Two: an alternative system becomes a candidate for “normal” because the compatibilities of its internal elements are more likely to persist than the incumbent system’s. They become persistent on a case-by-case basis, eventually reaching a critical mass of collective presence. The origins of the persistence may also be either authoritative or opportunistic.

Influence, however, may be circumstantial; and presence may be episodic. In both cases there must be a reason why the older system is vulnerable enough to be replaced.

An organization such as a company, a market, or an entire community can be a system… A system’s supportability is particularly sensitive to priorities. Priorities typically relate to competition, cooperation, or cohesion — the level of interaction on which changes originate. As support factors, those interactions correspond approximately to advantage, competency, and protection — the measured variables representing the priorities in the system.

Changes underlying the priorities have upstream influence.  Within a system, one’s own actions and the actions of other parties have consequences that either reinforce or undermine the priorities.

The Next Normal -Vulnerability Factors

 

Variations in inhibitions and encouragement alter support of the priorities; priorities support the compatibilities of system elements. Therefore, variations of the underlying factors potentially changes the equilibrium and the further predominance of the system. That change will invite a renovation of the system or deference to another (successor) system.

The most likely instigator of change is demand. The pressure of demand comes from how it amplifies some priorities at the expense of others. Then:

  • If demand alters the behavior of an organization, it may affect the equilibrium of related systems.
  • If a system becomes unstable, alternative interactions can find success and instigate rearrangement of elements within and around the originals, to favor new preferences in demand.
  • Consistent support of new interactions can mature into making the alternatives the next normal.