Context and IQ


Alan Kay is the source of two quotes I love:

1. The best way to predict the future is to invent it

2. Context is worth 60 IQ Points

Many enterprise and business architecture methods advocate aligning with business strategy. This alone indicates that they themselves are coming from another perspective than business strategy! In the case of methods like TOGAF® that is reflecting their history as IT Enterprise Architecture approaches.

We contend that Business Architecture and Strategy are inextricably interwoven. We also believe that the important stuff to worry about when doing strategy is “out there”, i.e. in the context, not internal. We have control over things like organisation structure, process, value stream (to an extent) and capabilities. What we don’t have control over, but which we absolutely must pay attention to in our strategy is the stuff out there, such as competition, legislation, social change, technology innovation, politics and the state of the economy.

It is absolutely vital that we understand our current context and future scenarios for how this will evolve before we choose direction and commit resources. For example, we don’t want to build a new internal combustion engine car model when we will not be allowed to sell it in a zero emissions future city. We don’t want to create a physical store to try to compete in an industry that has gone completely digital (e.g. music), unless, of course we have identified and are happy with a niche audience (e.g. those who prefer buying music on vinyl). We do not want to bring a service to market that legislation will prohibit us selling.

Understanding the context is vital to making sensible choices for future product and service offerings and hence the organisation, capabilities, partners, processes, technology, systems and data these will require. A good technique for considering contextual issues is STEEPLED, which stands for: Social, Technology, Economic, Environment, Politics, Legal, Ethical and Demographics. These are best considered in facilitated workshops exploiting scenario analysis techniques. We may also have to draft in participants with specialist knowledge.

Equally important is understanding all the Stakeholders and how we interact with them. These parties include Customers, Shareholders, Partners, Suppliers, Regulators, Unions, Industry Bodies, Related Companies etc. We like to do a Stakeholder Net Value Exchange (SNVE) model to identify what each party contributes and expects. This can be a brilliant starting point for downstream analysis including business events, value streams, process analysis and information analysis.

If you want more information on methods that integrate these perspectives and techniques, please visit inspired.org. There is also training, the Holistic Architecture Language and tools.

Intelligent Enterprise

I saw videos on Youtube addressing “Signs of intelligence” in people - one good one was from Success Formulas. Contemplating how intelligence translated to action creates value and how that applies to organisations vs people. So, here are 13 marks of intelligence in enterprises:

  1. Curiosity - A desire to be aware of, to know and to understand. This applies to the environment, competition, economy, technology and many other factors. Enhanced by open culture, available resources, sharing and availability of open channels and information

  2. Adaptability and Flexibility - Willing to change procedures, processes, ways of working for the better, especially based on facts and evidence. Supported by investment in research, training and mentoring. Encouraged by value driven culture

  3. Sense of Humour - Being able to find the funny in the absurd or adversity. Being able to see our own faults, recognise them, acknowledge, learn from them and move on

  4. Learning from Mistakes - Not just allowing mistakes, but actively learning from them and spreading the learning so we don’t make them again

  5. Versatile Memory - Recording things, organising things, sharing knowledge, use of ontologies, making knowledge explicit rather than than tacit. Supported by semantic technology, graph database, AI

  6. Emotional Intelligence - Paying attention to the people side, desires, aspirations. Creating a good culture which values individuals and looks to satisfy their needs, but also demands high standards and delivery

  7. Intellectual Humility - Our way is not the only way. We can always learn more. Take in research, see what competitors are doing, find new models. Being open

  8. Creativity - Sparked by open innovation, forums, pet projects supported by enterprise resources, some pure research just based on curiosity. Leaving space for serendipity

  9. Open Mindedness - Accepting of new ideas, diversity (age, race, gender, culture, language, income, values…)

  10. Effective Communication - In all forms. To the ecosystem surrounding us (Partners, Regulators, Industry Bodies, Interest Groups, Unions, Media, Employees, Public, Shareholders…) via various media. Also encouraging free and open communication internally. Creating collateral which clearly communicates who we are and what we are about

  11. Self Awareness - Reflection, good metrics. Knowing our strengths, weaknesses, opportunities and threats. Able to focus on what we do uniquely and well while outsourcing other things or improving them

  12. Strategic Planning - Thinking long term, but acting in the present in alignment with vision. Enhanced by business and enterprise architecture

  13. Range of Interests - Diversification. Not putting all our eggs in one basket / product / service or small group of customers. Being aware of the “adjacent possible” to come up with new, possible Blue Ocean offerings

Here’s to more intelligent enterprises in the coming year, leading to Desireable Futures.

Pareto and saying “No”

In contemplating the New Year and plans for the future, I came across a simple process by Vicky Zhao that looks at 1) Review 2) Plan 3) Prioritise using five techniques a) Pareto b) confirmation bias c) inversion d) "one thing" e) SMART objectives. I was struck by how similar these are to an architecture process and how we can exploit two of these ideas in particular.

The first is Pareto or 80/20 analysis in the review of past performance. Simply put, Pareto analysis tries to find the things that may have consumed 20% of effort or resources, but produce 80% of the desirable results. This is a great way to identify those things we should double down on in the future. If we can spend 60% of our effort and resources on them in future, we may be able to generate 3x the desirable results!

The inversion idea in planning is to start with the end in mind. We do this routinely in architecture through developing a vision or scenarios. We can then decompose this to identify what will be required to make it a reality. We can do this for several time horizons to give us short, medium and long term goals. Think Transition Architectures.

Next we need to ensure that we are not distracted or diverted from the focus we need to progress meaningfully and continuously. The “one thing” in the planning approach encourages finding just one key thing/theme to focus on per time horizon.

Steve Jobs extolled the virtues of focus powerfully:

"People think focus means saying yes to the thing you've got to focus on. But that's not what it means at all. It means saying no to the hundred other good ideas that there are. You have to pick carefully. I'm actually as proud of the things we haven't done as the things we have done. Innovation is saying no to 1,000 things."

Extending the architecture idea of gap analysis, we can look at:

  • Which things are on the 20% Pareto list? We should be saying “yes” to these and “no” to the others

  • What should we Stop doing? Many of the things in the 80% effort Pareto list can fall here

  • What should we Start doing? These would be things that support our goals and vision that are not already in our capabilities

  • What should we Change? This can include improvements in efficacy, quality or efficiency

Finally, we need to further decompose the goals remaining to objectives and ensure they are Specific, Measurable, Achievable, Relevant and Time Bounded (SMART).

Happy planning. Remember Pareto and the power of saying “No”. Also keep in mind this wisdom from James Clear, author of Atomic Habits:

“Goals are good for setting a direction, but systems are best for making progress”

Leveraging Assets

An asset was traditionally something you own which had value or which you could use to derive value. An example of the former would be cash or gold. An example of the latter would be an item of equipment.
We can update this in two important ways:

  1. Assets can be virtual or digital, so we could have something like a skill, a design, a patent or a recording

  2. We don’t necessarily have to own them to derive value from them

Some of the fastest growing and valuable companies do not own the assets they leverage. Uber does not own cars; AirBnB does not own accommodation; YouTube does not own the content it serves.

Virtual assets, such as a design, can be very valuable. We can profit from royalties, copyright, trademarks etc. without necessarily ourselves making the product or delivering the service. Consider the inventor of the crown bottle cap, William Painter, whose company received a royalty on every cap used for several decades!

Digital assets are also profitable. A music track is recorded once, but can be listed on thousands of websites virtually for free, then duplicated, again virtually for free and shipped to consumers, again almost for free. This can occur millions of times, generating substantial revenues while not parting with the original asset.

The best though, is using someone else’s assets to deliver value. Uber, for example, uses the assets of owners (cars), the assets of drivers (skill and time), the global infrastructure of the Internet (funded by advertising, corporates and governments) and the asset of the user (cell phone) to deliver a valuable and desirable service.

In doing business and architecture planning, it is useful to contemplate Asset Leverage.

First list assets. Look for things that you own, things that you know, things that you know how to do. Try to find things in the categories of physical (e.g. property, stock, equipment); monetary (cash, investments, shares, bonds etc.); knowledge/designs/patents (e.g. books, recordings, designs, models); virtual (e.g. skills, customer goodwill) and digital (e.g. recordings, images).

Next think about assets you do not own that you can leverage. Examples include those of Partners (e.g. supplier knowledge, skill, equipment, stock); Customers (e.g. premises, network, computing, cell phone, time); Investors (expertise, connections); Infrastructure (e.g. Internet, public facilities); other Owners of something you need (e.g. Accommodation, Cars, Images, Location data).

Figure out to what extent you are currently leveraging the assets. Look for opportunities to leverage them to a greater extent. A great deal of value can be unlocked this way. You can find the best opportunities by looking for those assets that can generate a lot of value that you can access with relatively little effort or expense.  

#businessarchitecture #strategy #businessanalysis #digitaltransformation #assets

Stumbling towards AGI (Artificial General Intelligence)

Elegant Architecture overcomes limited and messy implementation?

A new article discusses Hugging GPT which uses Chat GPT as a human interface and executive controlling module to control tasks to complete a goal. The tasks are delegated to specialist AI models that perform narrow functions well. The video discusses the ideas and is a great introduction to the paper.

Better Search: Will ChatGPT (or similar) displace Google?

Google has become indispensable in our work and personal lives. Finding products and services, checking out reviews, finding the cheapest supplier and doing professional research. Google has built a $150Bn advertising revenue business on top of that ubiquity.

The ChatGPT large language model from OpenAI burst on the scene recently, attracting over a million users in a week. It boasts a conversational interface accepting complex queries in natural language, a human language response and allows to refine our search, seek more detail or pursue other aspects easily. This style of interaction is extremely attractive - it’s a bit like having a hugely knowledgable human expert on tap to instantly understand our questions and answer in an accessible paragraph or two. It raises the question “Is this the future of search”? Fuel has been added to the fire of this debate with the investment by Microsoft of a further $10Bn in OpenAI. Remember that Microsoft has long promoted Bing in competition with Google search.

But not so fast… The results from ChatGPT are not always accurate. It is based upon a predictive model which has ingested huge amounts of data from the Internet and document sources. Because it is a mathematical model based on probability, it will favour average and mainstream opinions from its training set. It can be prompted to produce factually incorrect answers which are stated very convincingly as facts. Annoying if the recipient already knows the facts, but dangerous or misleading if the recipient does not. The model is also trained on this corpus of data at a given time, in a “batch” mode. So it may not reflect information recently published, or which has been updated since the last training cycle.

OpenAI and others wanting to promote these kinds of systems for search will have to find ways to improve accuracy and currency of the underlying models and provide caveats to users about potential bias and inaccuracy. Meanwhile, Google, which itself has significant AI systems and probably the best, biggest data sources to train them on, can easily add a conversational interface.

To date, ChatGPT has been offered for free use (to gain experience, publicise capabilities and refine the models), but this is likely to change very soon. OpenAI does not yet have in place an advertising supported model like Google and is likely to first try subscriptions. But when it is no longer free, other competitors will spring up.

One smaller but interesting player is looking to offer the best of both worlds, starting now. This is Andi (andisearch.com). Andi search lets you use GPT style prompts and provides a summary answer (much like ChatGPT), but also provides references and search results on the right to allow validation or further exploration. This is very promising! It should be an exciting time in search this year.

Dealing with Change

We probably all feel a little battered by the levels of change we are experiencing. Technology, pandemic, business models, social mores, ethics, sustainability, legislation and more. It is hard to retain our sense of perspective and balance and self worth when everything seems to be shifting around us!

As architects we are often the agents of change for the organisation, processes, products, systems and technology. But that does not mean we ourselves are always that happy with change! The threat is that it brings risk: Are we focussing on the right things? Are there new factors we aren’t aware of? Is our “known good solution” still relevant?

I find comfort in Jeff Bezos approach which advocates:

“Find what is not going to change and optimise for that”

He recommended, in the case of Amazon, that the following factors were unlikely to change:

  • Customers want cheaper prices

  • Customers want fast delivery

  • Customers want increased selection

And in the case of Amazon Web Services:

  • Customers want reliability

  • Customers want low prices

  • Customers want rapid innovation in adding APIs (increasing utility of the platform)

Find the things in your business / industry that will not change and optimise for them. 

Architecture as a Context for Agility

Agility requires doing focussed things rapidly. The more you know going in, the better decisions you can make quickly. The more you document what you learn, the more knowledge is available for future efforts. Good agile work fills in more of the picture thereby enabling all teams.

The more of the picture is filled in the more we can avoid wasted effort, align our efforts and deliver with less risk. You can’t create the full picture quickly, which is why many agilists avoid architecture.
But you can start with a “paint by numbers” reference model/ontology, which gives you the framework into which to rapidly record your growing knowledge and which indexes where to look for information for your next effort, and what touches the squares you want to colour, so you know how to be informed and compatible.

Every project (agile or otherwise) should:

  • Be informed by our knowledge of current architecture assets and challenges

  • Contribute to an improvement in assets, condition, effectiveness and future readiness

  • Improve the architecture of the portfolio

  • Deliver business value

  • Fill in more of the architecture “big picture” to inform future projects

The environment should:

  • Have a conherent integrative meta model/shared concepts

  • Encourage good work through well conceived principles

  • Have standards for how things get recorded (artefacts) so they are meaningful and sharable

  • Provide a collaborative repository that holds things and makes them findable

#agile #project #architecture #context

If data is the lifeblood, how’s your heart?

Organisations are paying more attention to data management, often driven by compliance, privacy or cyber security concerns. But simply holding data doesn’t generate value.

We need a thorough understanding of the relationships between data (numbers, text, pictures, audio, video, facts), information (data meaningful to humans: salary, sales, order, invoice, fingerprint etc), knowledge (richly connected data: contextual data, trend data, inference) and wisdom (deep insights, experience shaped). Value increases as we move up this hierarchy. Alongside that, if we are to understand what we have, manage it properly, secure it, use it, integrate it etc., we need meta data: data about data. Where is it from? How is it structured? Who owns it? How much can we trust it? How is it derived? What format is it in? Where do we keep it? How long should we hold it? What are the constraints on its use…

All of the above are complicated by the explosion of data brought on by new forms of data; technology capabilities to capture, store, manipulate, communicate, generate, represent and analyse data and innovative applications. Virtualisation of products and services compounds the problem, as more of what we offer and sell to customers is information rather than physical.

There are more opportunities than ever before to profit from data, information, knowledge and its proper use. But there are also more challenges associated with doing it properly, successfully, reliably and securely. All of these rely upon skills and capabilities. Specifically, we need high skills to understand, analyse, model, design and implement data related products and services. This is the realm of Data and Information Architecture.

Architects also need to understand business requirements, facilitate communication and build consensus, define vision, bridge gaps and scope initiatives. They need to guide projects and solution designers. Crucially, they need to connect the business/conceptual view of data with the logical (application) and physical (database and technology) views. They need to devise, apply and encourage use of good principles to evolve the data and information landscape in positive ways.

Data management is ultimately a business responsibility, but can be assisted by many technical skills, including: maturity assessment, modelling, meta data management, technology architecture, risk analysis, integration design and considerations of security and privacy.
A comprehensive data/information architecture and data management capability is vital to deliver business benefits as well as ensure security, privacy and acceptable risk.

These are all topics covered in depth in our Techniques and Deliverables of Information Architecture intensive online live course from the 7-11th November. See details here.

#dataarchitecture #informationarchitecture #digitaltransformation #bigdata #businessintelligence #bi #datamodelling

What comprises a “Solution Architecture”?

A solution is a combination of components in a configuration that solves a problem or exploits an opportunity in a way that meets our goals. Hopefully it is also effective, efficient, sustainable, ethical and relatively risk free.

It is not just a software system, but rather a combination of software, process, people skills, data and technology that meets business, human, technical and legal requirements.

Considering the provided rich picture:

The items outside the circle represent the context in which a solution is developed. We ignore these at our peril. If we do not know the Business Goals for a solution, we can only meet them by extraordinary luck. If we do not know the Legal constraints we will run foul of the law. If we do not understand the Customer and the Stakeholders, we are unlikely to provide something they are happy with. If the service is not delivered via the required Channels or compatible with the Brand strategy, we may miss the mark entirely. In short, many of these should inform our Requirements. Alan Kay famously remarked: Context is worth 80 IQ Points.

Our requirements should also certainly include the Functions that must be performed, the Business Objects (Data) that is used, the Technology we need, the Process to deliver Value, the Application Services we may use or provide, the User Interfaces, the Events we need to respond to or generate and the Locations where we need to be available.

Non-Functional requirements will also play a major role in the viability and success of a solution. These include aspects such as security, reliability, performance, cost, maintainability, flexibility, ease of use, compatibility and many other factors.

Customer Experience is crucial to ensure wide and willing acceptance and delivery of business value. Staff experience is also key, as it that of other professionals who will deal with the solution, including Operations, Support and Maintenance staff.

The Solution Architecture should follow some important principles, including: Modularity, loose coupling, message based communication and open standards. Its also good to have tests built in and automatically repeatable, an affinity for DevOps or Continuous Deployment. User interfaces that are intuitive and built in tutorial aids are really important too.

A cost effective system might be composed of off the shelf components, reusable library elements, configurable components and custom developed elements. The solution includes these and the other elements of human skill and capability, supporting technology, infrastructure, documentation etc.

We may also need to contemplate the development/ implementation dependencies and partition the solution into an initial Minimum Viable Product plus one or more incremental delivery releases to get us to the full capability required.

Solution Architecture is a challenging but very rewarding role.

#SolutionArchitecture #Architecture #Requirements