I try to think about architecture in simple terms. Architecting is about connecting the dots (physical, perceptual, conceptual, financial, and temporal).
Construction (of systems, structures, and capabilities), is focused on a fixed snapshot of dimensions (time, geography, resources, …). Construction must work for today’s needs (as we understand them from multiple stakeholders).
Architecture helps reduce the complexity of today’s world (multiple dimensions amidst an accelerating pace of change) to improve the clarity for what is designed and how it should be constructed and to help ensure that the solution (whatever is constructed) can adapt to known and unknown needs of stakeholders (some call this sustainability and adaptability) over time.
The challenge with architecture has been the limited knowledge about the geometric growth in complexity and our inability to “predict” (anticipate) the needs of the stakeholders in the future. The advent of Big Data and Big Computing may help solve that, but that’s probably another article or two…
Everyone has the desire to make an impact (on various levels) throughout their lives. The challenge is to find folks who “think” like we do and have the desire and resources to act up on aligned thoughts to effect change (could be on any dimension). But, most of our time is spent convincing others about “our ideas” and then trying to get them to apply resources (their time and money…and perhaps others) to implement those ideas. That is why so much time and money is spent on marketing, sales, and consulting analysis (not necessarily implementation). The challenge for all of these folks is trying to get someone (lead, customer, member, partner, associate, or even a friend) to “see” the problem or opportunity with clarity. The challenge is that the way the problem or opportunity is framed, can bias the reality (and scope) for what should be done and the best approach to apply in achieving the right results.
We see this every day as these discussion unfold between provider and consumer (and yes, between physician and patient). The challenge for the consumer is one of framing. How do they frame the problem and/or opportunity so that it represents what is contextually relevant to the jobs that they are trying to get done ? How do they know that the right scope is presented and that they are solving the right problem or that the right solution is being applied (even if they know the problem is properly framed) ?
Consumers are fairly adept at matching a products/service which meets their needs once they can connect the dots between a properly framed set of unmet needs (problem or opportunity) and the capabilities and results (perhaps laid out in a story or shown as demo) that are offered by a product or service. But, the challenge for the consumer is how do they frame their problem / opportunity in an environment where the level of complexity and the pace of change is accelerating. [we used to live in a world where “change happens”, that’s still true but it’s no longer constant change, now it’s accelerating]
We now have the capability to “see” more clearly when identifying problems or opportunities. The advent of Big Machine processing (democratized parallelism in computing…if you will) and the availability of Big Data (the amount of available data that helps us properly frame the problems / opportunities in their entirety) can be used to create better awareness and understanding. Big Data (not a fan of that term, but it is popular), has the potential to transform organizations and the age-old dynamic between provider and consumer (esp. in Healthcare). This “potential energy” (if I can use that metaphor) will likely remain in that state until the data can be properly framed by contextual relevance (let’s call the metadata for now).
Example of contextual relevance:
Suppose I come across a new tool. I have never seen this before and would have no desire to use it (let alone purchase it). Then, I see another customer walk up to that tool and talk about how “he/she” uses that tool on her job. I don’t have the same job as this other customer, but I am trying to get similar things done around my home …AND this tool suddenly becomes relevant once I understand how it can be applied and used. Of course, I might see a neighbor using the same tool for a very different purpose and discover yet more uses for the same tool The tool has not changed, but my awareness and understanding of how to use that tool has been expanded and THAT increased contextual relevance allows me to further leverage the same tool.
Just imagine how contextual relevance can impact the way we use data to help us get our jobs done. Now, you can get a glimpse of the power of data and the importance of framing it (using contextual relevance) to realize the full value it can provide. Again, the availability of data exists, but it’s only useful once we can use it properly to gain awareness and understanding.
Now, we come to the next problem that compounds complexity and challenges consumers ability to clearly understand a given problem or opportunity. The amount of data that exists is already more than we can consume. So, our old reliance on reports and 2nd generation analytics (multi-dimensional cubes), are fast becoming irrelevant. We need a new way of conveying understanding with the growing amount of data. Conventional approaches for conveying awareness and understanding (let alone attempting to explain how a product / solution can address the consumer’s unmet needs) is becoming increasingly difficult. Here’s where advances in visualization need to be brought forward because Big Data is a compounding problem and conventional methods of conveying awareness and understanding through reports, dashboard, and analytics are simply not able to conquer the data or the growing number of patterns that may exist in the data. Providers tend to “simplify” the complexity since they themselves are overwhelmed or there are some who are leveraging (and even pioneering) techniques in visualization to help improve their ability to communicate awareness and create understanding.
Example of visualization opportunities:
Imagine (in a few years) when your DNA will be available for your doctor to review along with your EMR (electronic medical record) and statics from the CDC and other sources may be brought together for a diagnosis for your overall health and/or a medical problem (in specific). The conversation might be awkward at best if the doctor does not have a command of the patterns (that pertain to your immediate problem) and worse if the doctor cannot identify probabilities of causality or perhaps indicators for predicting mortality (you might die and you won’t identify root cause until it’s too late). There is simply way too much information for the physician to “mine” through using conventional tools. A whole new set of tools will need to be brought forward so that your physician (and any other physician for that matter) all see the same pattens and indicators to properly guide diagnosis and treatment. Even better, is the enormous amount of data that can be brought to bear on the side of prevention, which would bring costs down for healthcare in general. But again, this would only exacerbate the complexity facing physicians with diagnosis. So, these are just a few “use cases” where improved techniques in visualization are needed to augment awareness and understanding.
Putting it together
So, we have Big Data, we have Big Machines, we are building and extending our contextual relevance around all this data and we’re seeing advances in visualization to help create awareness and understanding. The potential for applying this in helping consumers more fully understand their problems / opportunities will greatly sharpen the focus for the providers in identifying solutions that meet the consumer’s unmet needs. The possibilities are endless…now all we have to do is spend some time to understand how to capture and measure unmet needs for customers (see earlier posts) and marry them up to the patterns of problems and opportunities to complete the mapping exercise to solutions (products + services).
At any given time, one or more architectural disciplines (business, application, technical, information,…) may be applied throughout various phases of a project, which is managed using one or more methodologies within the discipline of project management. I see PM as one of many non-architectural disciplines that are used throughout the course of a project. What I think is missing is something I call Implementation Architecture (which I rely upon) to manage the flow of change used to implement new and/or improved capabilities across the organization. The question raised by Jason is interesting because it calls into question the narrow scope of PPM, which typically only focuses on the portfolio of projects and not the multitude of portfolios across the entire organization (which may be involved in manifesting change). That is where I use Implementation Architecture as the missing architectural discipline within EA to address the structures and relationships between all these portfolios to ensure change is implemented properly once defined by the business and/or operations.
I use Solution Architecture to produce a snapshot of changes that need to be implemented to address (one or more) issues and/or opportunities. Each one of these solution architectures may produce a series of projects, which can impact one or more portfolios within the organization. I use Implementation Architecture to manage these “mini-portfolios” of change and rationalize them against the larger set of portfolios across the organization. Implementation Architecture addresses the complexity of managing change across the numerous Solution Architecture “portfolios” to ensure change flows properly across the organization and the value chain (dealing with multiple domains, multiple dimensions, and even more complexity).
Traditionally, the Business Units are responsible for the Lines of Business (products & services) used to deliver value to consumers (customers who purchase / consume their products & services). The Business Functions exist to support and/or serve the needs of the Business Units (directly and/or indirectly) with variations of granularity (based on where they are situated within an organization where the visibility is seen thru functional breakdown). Due to the highly distributed nature of organizations and expanded scope of services that are now being delivered to customers, the lines are no longer crisply drawn between BUs and BFs. That’s a good thing since businesses are discovering new ways of extending value of their internal services (especially from a B2B model). That may suggest that we need to consider shifting away from the way we perceive (and subsequently define) the business organization (BUs and BFs) and embrace businesses as a series of one or more supply chains designed to provide services within and without a given organization.
It’s a more dynamic and organic business model that allows architects to define things within a “flow-based” service model (which is where most of our systems of systems thinking is moving) and away from the “discrete” functional models, which was derived from our industrial manufacturing mindset. This new approach also creates a more fluid perspective around planning and may create more innovation opportunities for the way organizations are conceptualized, managed, and operated.
I can just imagine how this might shift the discussion around the definition of architecture and that of the enterprise in future discussions.
Here’s one way to think about positioning EA Services your customers:
The customers for EA are all the participants that may be impacted by services provided by EA (one or more individuals) within a given scenario (or set of scenarios). One Example: Suppose EA services are requested for a small manufacturing organization to look at their product development capabilities. Depending on the scope of the engagement / problem, the EA may need to consider the external consumers of the product(s) in addition to the following internal customers of his/her services: (executive mgmt, functional areas like finance, marketing, legal, compliance, product mgmt, product dev staff, and operations staff) and even the market (if publicly traded). At first glance, this may appear too large (btw, I didn’t even include the partners and the environment – from a sustainability perspective). It’s complicated and filled with uncertainty…an ideal situation for EA 🙂
In specific, think about aligning your customers and markets w/in the scope of EA:
When examining the categorization of the supply chains and value chains (via markets and segmentation), the mapping exercise can get even further complicated when trying to capture, map, and align the patterns of desired outcomes across all these “customers”. This is where the EA can provide a lot of value to CMOs and product marketing/dev teams.
But, it’s complicated…I just want to focus on simple solutions and pragmatic approaches:
The above responses would appear to bely the notion of simplicity in providing a pragmatic approach. The scenario for product development is by its very nature a highly complex orchestration of distributed activities and jobs. There are always ways of abstracting complexity through agreed upon reference models and assumptions, but then the question of risk comes into play as to the precision required to deliver the right products for the markets and/or market segments.
I think the EA can provide services to address any level of complexity, but the EA also needs to provide a balanced set of insights on risk to guide the decision makers appropriately.
An often asked question involving Enterprise Architecture (EA) is “What role should EA play when organizations are implementing an ERP ?“.
Let’s look at the core role that an ERP plays in an organization (which typically enables the transaction management and ensures compliance in one or more domains covering order through cash cycle and down through SCM & logistics). While that’s a large portion of the operations management for an organization, it is not the value differentiator. In many cases, the ERP vendor and/or organization has attempted to “extend” the core features into these value differentiating areas. This is where things get tricky when organizations need to move with “agility” (whatever that means…) or need to merge operations (M&A) or divest or (gulp) integrate with other organizations. Most integration topologies are now being built atop the embedded ERP middleware solutions. This gets tricky also since the number of interfaces and the complexity of these “exchanges” is growing exponentially due to the pace of business and the opportunity to collaborate. And, we haven’t even begun to talk about “Big Data” (which bleeds over from operational to value differentiation) and presents an order of magnitude more complexity.
I would think that an organization would want to engage EA to influence the positioning of the ERP and guide the configuration of the underlying models used to meet the operational needs and enable the value differentiators for the organization (now & into the future). The challenge for the organization is how well it understands this balance and whether it is prepared to embrace the investments required to manage it (or simply follow the vendor and be managed by the vendor).
The challenge for the EA (based on how they are positioned in the org.), is how well he/she can communicate the complexities, challenges, and opportunities to obtain understanding and buy-in from the organization to ensure the right decisions are made to preserve this balance and sustain it as the pace of change accelerates.
Do you find it interesting that the majority of articles about IT & the business talk about this bridge, chasm, semantic layer, etc. ? When you look at companies struggling with growth, they too seem to talk about their own difficulties trying to improve their connection with their customers (either through requirements or loyalty programs). IT is as much tool-centric as most companies are product-centric. The challenges are similar in that both struggle to connect with their customers (internal or external). At least product managers and business leaders try to identify “trends” and opportunities with customers and some actually implement requirements engineering to ensure the products address the needs. Most IT shops have very little understanding of customer needs (whether from functional areas or LOB). They rely on packaged solutions (and little or no customization) to solve homogenized patterns of needs. Very little differentiation takes place here, since the designs and data models are often locked in by the vendors. Very few shops have software engineering capability, so they have to rely on vendors or 3rd parties to stitch the systems together so they can provide reports/analytics, and manage vendor support. There is little opportunity or interest in mining internal customers for their needs using a customer focus discipline. Is there any wonder why there is such a disconnect ? An EA can present integration frameworks, introduce customer focus processes, and even present models for improving analytics and aligning portfolios to streamline change management.
BUT, if IT is not able to measure value from the Customer POV, then it is very difficult to make the business case which enables IT to cross the chasm. Countless meetings will not overcome the lack of customer focus discipline. As a result, there will be little meaningful change to the bottom line. Disciplined measurement is the only way to identify, create, and deliver sustainable value. That’s the way it works for successful companies and that’s the way it works for IT departments who become integral to the company’s strategy.
Enterprise Architecture helps us address the following types of questions…
•Do the core business & operational structures support the strategic goal ?
•What do our customers want & how should we capture & mine this information ?
•How do we align strategy with tactical execution ?
•How do we measure value ? AND How can we platform value delivery ?
•How do we leverage risk to drive the right decisions ?
•Are the functional processes, controls, and metrics aligned across the org ?
•Are the x-functional operations properly modeled and aligned to enable the functional areas ?
•Are service levels and metrics models aligned to support the internal & external needs ?
•How do we ensure operations can adapt to business change in an agile manner ?
•What are the information needs to support the operational controls and metrics ?
•How do we manage the data quality and data security needs to address business risk ?
•Do the data structures and logical models support the needs of the business & operations ?
•How do we accelerate the “right” decisions across the value chain (not just mgmt) ?
•Why do we need to manage the lifecycle of data and how do we impart governance ?
•How do we become a “learning” organization (beyond managing knowledge) ?
•How can we harmonize business rules & constraints across the enterprise ?
•How do we ensure technology works for our customers (instead of the other way around) ?
•How can technology be designed & implemented to drive business agility ?
•How do we ensure IT & Business folks talk one language ?
•What are the right technology platforms to support the value platforms for the organization ?
•How do we build and/or source a set of reusable services used within & without UL ?
•How do we approach a virtualization strategy that optimizes corporate resources ?
•How do we leverage virtualization to accelerate change management ?
•What types of computing platforms and topologies will support growing information demand ?
•How do we enable ubiquitous computing w/in the enterprise & w/o the extra-prise ?
•How do we shape vendor relationships to enable flexibility while supporting sustainability ?
•How do we align the multiple portfolios across the enterprise ?
•How do we ensure execution enables strategy ?
•How do we align customer needs, organization priorities, and requirements through design, build, testing, and delivery ?
•How do we measure value delivery for customers (internal & external) with projects ?
•How do we ensure we design, build and deliver products and services that meet the desired outcomes of customers ?
•How do we ensure that technical platforms address the needs for value platforms ?
•How do we optimize human potential (intellectual capital) in value delivery ?
•How do we enable a culture driven by learning and continuous improvement ?
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