1 year, 2 months ago

Designing Digital Change

Session Synopsis for Hong Kong, April 2016: 

In this session Mr. Nigel Green shares his experience of preparing organisations for the Digital World. He introduces key concepts that will help open-up the discussion of the implications, risks, and opportunities, of a digital strategy. Whilst the popular definition of “Going Digital” is often focused on digital channels for Marketing purposes, Mr. Green explains why it also impacts many areas of the organisation, and explains why it is not simply the CMO’s, CDO’s, or CIO’s challenge alone. He will also share tools and techniques used in the design & execution of the transformation to a digitally enabled business. In addition, he will discuss pragmatic next steps to take, and share ideas on how to contribute to a business-wide discussion on the subject.
This session should be of interest to anyone trying to get to grips with what “Going Digital” means to their organization, and how to start planning the change:
  • The components of a digitally-enabled Business Model
  • The implications & risks of adopting “Bi-modal IT
  • How to design for the protection of existing core business systems whilst embracing the new
  • Dealing with an unknown future, and adaptive long-range planning
  • The dangers of “Big Design Up Front”, and perhaps paradoxically, why “Adaptive Design” is ever more crucial
  • The business and technology architecture implications – including a perspective on the applicability of a pattern adopted by the “born digitals” (e.g. Netflix, Google, and Amazon)
  • Suggested subject matter experts to track, follow-up research material, and next steps to take.

1 year, 2 months ago

Designing Digital Change

Session Synopsis for Hong Kong, April 2016: 

In this session Mr. Nigel Green shares his experience of preparing organisations for the Digital World. He introduces key concepts that will help open-up the discussion of the implications, risks, and opportunities, of a digital strategy. Whilst the popular definition of “Going Digital” is often focused on digital channels for Marketing purposes, Mr. Green explains why it also impacts many areas of the organisation, and explains why it is not simply the CMO’s, CDO’s, or CIO’s challenge alone. He will also share tools and techniques used in the design & execution of the transformation to a digitally enabled business. In addition, he will discuss pragmatic next steps to take, and share ideas on how to contribute to a business-wide discussion on the subject.
This session should be of interest to anyone trying to get to grips with what “Going Digital” means to their organization, and how to start planning the change:
  • The components of a digitally-enabled Business Model
  • The implications & risks of adopting “Bi-modal IT
  • How to design for the protection of existing core business systems whilst embracing the new
  • Dealing with an unknown future, and adaptive long-range planning
  • The dangers of “Big Design Up Front”, and perhaps paradoxically, why “Adaptive Design” is ever more crucial
  • The business and technology architecture implications – including a perspective on the applicability of a pattern adopted by the “born digitals” (e.g. Netflix, Google, and Amazon)
  • Suggested subject matter experts to track, follow-up research material, and next steps to take.

1 year, 8 months ago

Going Digital & Agile Architecture

Recently, I’ve been reworking & tightening-up some earlier ideas and putting them in a ‘Going Digital’ context. I’m posting them on LinkedIn to reach a slightly different audience.  
Here are the posts so far:


During the process, I’ve been reading/re-reading some great related articles that discuss agile architecture and the need recognize the business as a complex adaptive system. Here are the links with some favourite quotes:

Is Agile killing EA #1?  by Charles Betz the EA team needs to match the cadence of the Agile teams. This is a central challenge”.

Is Agile killing EA #2?  by Jason Bloomberg.

” …if some company’s EA means nothing more than a lot of paperwork that gets in the way of basic goals like working software that keeps customers happy, then we can only hope Agile drives a nail into that coffin. On the other hand, sometimes paperwork is a good thing. Only an overly dogmatic reading of the Agile Manifesto would lead one to conclude that we don’t need no stinkin’ documentation”.

“Frameworks are cocaine for executives – they give them a huge rush and then they move to the next framework”.

Enterprise Architecture Finally Crosses the Chasm by Jason Bloomberg including an interview with Adrian Cockcroft formally the Cloud Architect at Netflix. 

“The goal of architecture was to create the right emergent behaviors”.

“..it makes more sense for them to pay most attention to the real-world  ‘wiggliness’ of organization: the hidden, messy and informal dynamics of everyday human interaction in which they and everyone else are continuously immersed”.

With the ‘Going Digital’ series, my aim is talk about real-world experiences and emerging techniques for doing “agile architecture’, or business change design, or whatever it gets called in the future. All I know is that it isn’t framework-centric and that many who carry the title Enterprise Architect will have trouble giving up their particular drug of choice! I’m interested to hear what others are doing; what’s working for you – and what doesn’t.

I guess like many of have lived with the ‘EA’ label, I’m tending to avoid the term, so as not to confuse what I do with the framework-centric, heavy modelling, and ‘certified’ practices stuff.

Has anyone seen a good job description? 🙂

1 year, 8 months ago

Going Digital & Agile Architecture

Recently, I’ve been reworking & tightening-up some earlier ideas and putting them in a ‘Going Digital’ context. I’m posting them on LinkedIn to reach a slightly different audience.  
Here are the posts so far:


During the process, I’ve been reading/re-reading some great related articles that discuss agile architecture and the need recognize the business as a complex adaptive system. Here are the links with some favourite quotes:

Is Agile killing EA #1?  by Charles Betz the EA team needs to match the cadence of the Agile teams. This is a central challenge”.

Is Agile killing EA #2?  by Jason Bloomberg.

” …if some company’s EA means nothing more than a lot of paperwork that gets in the way of basic goals like working software that keeps customers happy, then we can only hope Agile drives a nail into that coffin. On the other hand, sometimes paperwork is a good thing. Only an overly dogmatic reading of the Agile Manifesto would lead one to conclude that we don’t need no stinkin’ documentation”.

“Frameworks are cocaine for executives – they give them a huge rush and then they move to the next framework”.

Enterprise Architecture Finally Crosses the Chasm by Jason Bloomberg including an interview with Adrian Cockcroft formally the Cloud Architect at Netflix. 

“The goal of architecture was to create the right emergent behaviors”.

“..it makes more sense for them to pay most attention to the real-world  ‘wiggliness’ of organization: the hidden, messy and informal dynamics of everyday human interaction in which they and everyone else are continuously immersed”.

With the ‘Going Digital’ series, my aim is talk about real-world experiences and emerging techniques for doing “agile architecture’, or business change design, or whatever it gets called in the future. All I know is that it isn’t framework-centric and that many who carry the title Enterprise Architect will have trouble giving up their particular drug of choice! I’m interested to hear what others are doing; what’s working for you – and what doesn’t.

I guess like many of have lived with the ‘EA’ label, I’m tending to avoid the term, so as not to confuse what I do with the framework-centric, heavy modelling, and ‘certified’ practices stuff.

Has anyone seen a good job description? 🙂 

Update Feb 27th 2017: To see where these thoughts now are going please take a look at the Found In Design un-book  and  the Horses and Unicorns story.

1 year, 11 months ago

Design Patterns for Event-driven Distributed Intelligence

Following recent discussions with @seabird20  and @darachennis, I decided to publish a rough idea of the event-driven Distributed Intelligence architecture for Smart Grid (this could apply to the broader IoT). This is loosely-based on the microservices concepts & principles described here and builds on Duke Energy’s collaboration on interoperability and distributed intelligence initiative. The purpose of this post is to generate ideas and aid the ongoing dialogues. A fasr as I’m aware, the additional concepts I discuss here, that is SEDA, microservices and distributed agent patterns, are not  called out in the Duke Energy work (although the authors might reasonably claim they’re implied). My aim, however, is to make the ‘software and event data’ conceptual architecture much more explicit in this discussion.
Having said that,  the  first diagram looks pretty physical! It serves as a simple IoT-ish context: A metering sensor talks to an edge processor on a ‘Field Area Network’ and thereafter data is relayed back to the Data Centre for further processing.

In the 2nd diagram we open up the Edge Processor and to reveal a relatively simplistic view of the software architecture. This is based on the micoservices pattern described by Fred George, and my own experience as VP Product Development/Architect at VI Agents.




I found the concept of small, autonomous agents, work very well for us at VI. Moreover, I spotteda lot of parallels with Fred George’s description of microservices:

Publish anything of interest – don’t wait to be asked, if your microservice thinks it has some information that might be of use to the microservices ecosystem, then publish-and-be-damned.



Amplify success & attenuate failure – microservices that publish useful information thrive, while those that left unsubscribed, wither-on-the-vine. Information subscribers determine value, and value adjusts over time/changing circumstances.



Adaptive ecosystem – versions of microservices are encouraged –may-the-best-service-win mentality introduces variety which leads to evolution.



Asynchronous & encapsulated – everything is as asynchronous as possible – microservices manage their own data independently and then share it in event messages over an asynchronous publish-subscribe bus.



Think events not entities – no grand BDUF data model, just a cloud of ever-changing event messages – more like Twitter than a DBMS. Events have a “use-by-date” that indicates the freshness of data.



Events are immutable – time-series snapshots, no updates allowed.


Designed for failure – microservices must expect problems and tell the world when they encounter one and send out “I’m alive” heart-beats.



Self-organizing & self-monitoring – a self-organizing System-of-systems’ that needs no orchestration. Health monitoring and other administration features are established through a class of microservices.



Rapids, Rivers & Ponds
I also particularly liked Fred’s use of the labels Rapid and Rivers to describe two seperate instances of message brokers and Ponds to describe persisted data. Again very similar to the VI SixD architecture where we collected signals on a ‘Rapids’ bus and  business event & document messages flowed over a ‘Rivers’ bus, and Event Logs & Document Queues were our  ‘Ponds’. But that was back in 2002,  I do think the microservices pattern is much more elegant and more extensible.


Stage Event Driven Architecture
The 3rd diagram overlays what I see as the SEDA Stages in our Smart Grid architecture:

Stage1: Raw signal filtering, simple aggregation& correlation, negative-event detection etc.

Stage2: Goal and role based functionality via an ‘Edge Agent’ that does complex aggregation and correlation, sense-making and alerting. These might be implemented as microservices, or at least, share many of the attributes described by Fred.


Stage3: There will  be more aggregation & correlation, routing alerting and broadcasting done here. The junction of Information Technology (IT) and Operational Technology (OT)  is probably here. These are the the software components that sit back at the Data Centre, that receive and process the event messages produced by the ‘Edge Agents’. There’s also a nod to some sort of management console and the publishing of commands and requests to the ‘Edge Processing’ domain. This diagram is very sketchy right now, with loads of components missing.   I just want to keep things very simple at this stage. 

Stage4: This is where the  ‘Big Data’ heavy-lifting of historical data and predictive analytics stuff is done.

We used  the SEDA pattern to define an Events Network that was capable of processing 4bn events per day without having to invest in massive network bandwidth and huge back end processing capabilities for the Royal Mail – I believe the U.S. postal service didn’t implement a SEDA  and  throw a huge amount of cash at the problem. I love the elegance of a series of cascading queues that gradually whittle the tsunami of raw signals in real time, down to ‘right-time’ stream or tap of business-meaningful messages.


This is the early stage thinking and part of a much bigger Smart Grid, and ultimately Smart City architecture. Please feel free to tweet about. or better still, comment below. Thx.
2 years, 2 months ago

What’s A Strategy?

 Link to article
Recently, I was asked this simple question: What is a strategy?
According to this article a business strategy is: the result of choices executives make, on where to play and how to win, to maximize long-term value

Which seems reasonable enough definition, for the CEO, but doesn’t really help those who need to think strategically about other initiatives,  like, for example,  business change programmes. 

Here’s some thoughts on what a strategy is, and what it isn’t:


A strategy:
– Tells a story

– Is future focused

– Can apply to short, medium on long term futures

– Provides focus on what is important (and what isn’t)
– Is actionable

– Is a framework for decision-making

– Is holistic – considers changing environment & external events

– Examines alternatives

– Assesses risks

– Takes step back from Business As Usual – it is an abstraction from the current operation
– Can be emergent and living: will undergo revisions and course-corrections.
– Is a reference point for dealing with emergent change
– Is ‘WHY’, ‘WHAT’, ‘WHEN’ and ‘HOW’ focused. The ‘HOW’ in a strategy is a ‘Meta-HOW’:  often speaking to unknowns and unplanned (unknowable) events. The ‘WHEN’ is often more sequence focused than time-definite


– Is a choice

What a strategy isn’t:

– A detailed plan of activities

– A grand design

– A set of desired aims/objectives ( although these might be the basis)
– A mission statement

– A budget plan

– A collection of pre-determined projects

– A list of possibilities (technology-based or otherwise)

– Only applicable to ‘big’ or ‘long-term’ change (things often labelled as ‘strategic’).

Addendum:
I recommend reading Roger Martin’s wise words on the subject of Stategy.  A few quotes from his post:

The problem with a lot of strategies is that they are full of non-choices. Probably most of us have read more than a few so-called strategies that say something like, “Our strategy is to be customer centric.” But is that really a choice?”

I would argue that 90 percent of the strategic plans I’ve seen in my life are really more accurately described as budgets with prose”.

If you’re into destroying innovation, two words—”prove” and “it”—will do the trick”.

2 years, 2 months ago

A Wiggly Path To Transformation

According to Sunday Times journalist, Carly Chynoweth, “Managers must learn how to adapt so they can solve problems they haven’t faced before.”

And:

“The fundamental impression they give is that the future can be organised and managed to achieve what you set out to achieve, and as long as you do it right it will come out as planned. But the reality is much more complex. Organisations are wiggly. They don’t operate in the neat, straight-line way conventional management thinking assumes”.

“It is not possible to predict outcomes — they emerge from people’s actions. You might have plans about what you are doing, but so does everyone else.”

****
The culture and traditions of 100 year old Utility business make behavioual change hard. Power-plant Engineer’s detailed and precise planning techniques don’t work for this sort of long-term change. In our case, over 70% of the business processes will change. The main hurdle for us was the lack of certainty and predictability over 5, 10 and 20 years. It was impossible to answer the basic questions; when, how and how much? There was discomfort over sanctioning any plans without the ‘details’. This resulted in a period of ‘decision-making-block’.



This is when we introduced ‘Transition State’ planning. This borrows ideas from Complexity Theory: Specifically, the characteristics of Complex Adaptive Systems. We started with the premise that we cannot predict the long range future.  We also accepted that outcomes will emerge at various points along the way.


Much like ’Scenario Planning’, we first developed a few hypothetical ideas. These were refined in workshops with subject experts until we reached a reasonable consensus of:
  • the principles we will apply to different aspects of the transformation ahead of us,
  • an initial guess of when certain outcomes are needed,
  • a list of the main influencing events/decisions assessed as ‘Known’, ‘Unknown’ or ‘Unknowable’ now – along with an assessment of risk.

Armed with this, we plotted-out a series of ‘Way-points’ over time. We call these ‘Transition States’. Each has a few goals (expected outcomes) that we estimate to complete.  At this stage, Transition States are not pinned to a hard date.  Rather they describe the sequence of outcomes, and roughly when we think they’ll happen. Transition States are re-planning points; a time to reassess and re-estimate the next phase of work. The Transition State is an opportunity to amplify value-adding and extinguish value-detracting aspects.


After a few iterations, a more precise view emerged of the early Transition States and a traditional approach to planning and deliverables could be applied.


At first, we were quite concerned that this approach would be rejected by the culture; a plan must be very detailed and accurate before work can start. This, however, wasn’t the case, decision-makers could see the merits of a more agile and iterative approach to complex change. They liked the way ‘doable’ increments became clearer after a few iterations. They also liked the explicit opportunities for re-think and course-correction.



****
Is a Complex Adaptive approach the only way to manage large-scale, long-running, change? I’d like to hear how others approach designing and managing business transformations and whether they see the merits of Complexity Theory that we’ve seen, 
2 years, 11 months ago

Microservices and the Internet of Things – First impressions

I must say I was sceptical when I first heard the term “microservices”. It sounded like yet another wash-rinse-repeat cycle of earlier incarnations of SOA. It appears I was wrong – this architectural pattern has some  interesting characteristics that, in my opinion, offer some real potential for event-driven, edge-processing systems (that are prevalent in the Internet of Things).
After watching Fred George’s video, I realised what he described was an event-driven, agent-based, systems’ model, rather than how many of us see SOA implementations today (often way-off the original notion of a SOA). At a conceptual level, the pattern describes a ‘Complex Adaptive’ system.  Essential principles of the architecture, however, appear teasingly elegant and simple. Few of these design principles are unique to microservices, but in combination, they make a compelling story:
Publish anything of interest – don’t wait to be asked, if your microservice thinks it has some information that might be of use to the microservices ecosystem, then publish-and-be-damned.



Amplify success & attenuate failure – microservices that publish useful information thrive, while those that left unsubscribed, wither-on-the-vine. Information subscribers determine value, and value adjusts over time/changing circumstances.



Adaptive ecosystem – versions of microservices are encouraged –may-the-best-service-win mentality introduces variety which leads to evolution.



Asynchronous & encapsulated – everything is as asynchronous as possible – microservices manage their own data independently and then share it in event messages over an asynchronous publish-subscribe bus.



Think events not entities – no grand BDUF data model, just a cloud of ever-changing event messages – more like Twitter than a DBMS. Events have a “use-by-date” that indicates the freshness of data.



Events are immutable – time-series snapshots, no updates allowed.


Designed for failure – microservices must expect problems and tell the world when they encounter one and send out “I’m alive” heart-beats.



Self-organizing & self-monitoring – a self-organizing System-of-systems’ that needs no orchestration. Health monitoring and other administration features are established through a class of microservices.



Disposable Code – microservices are very, very small (typically under 1000 lines of code). They can be developed in any language.



Ultra-rapid deployment – new microservices can be written and deployed with hours with a zero-test SDLC.

It struck me that many of these design principles could apply, in part, to a 2020 Smart Grid architecture I’m working on, and to the much boarder ‘Internet of Things’ecosystem.

The microservices pattern does seem to lend itself to the notion of highly autonomous, location-independent s/w agents that could reside at the centre, mid-point or edge of an environment. I can imagine that the fundamental simplicity of the model would help, rather than hinder, data privacy and protection by being able to include high-level system contexts, policies and protocols (e.g. encryption and redaction) applied to the event-streams. This pattern, of course, won’t be the ‘right-fit’ for all situations, but it does seem to offer interesting opportunities in:

  • Agility – very small disposable services are deployable within hours
  • Resilience – withstands service failures and supports service evolution
  • Robustness – it’s hard to break due to: simplicity, in-built failure handling and lack of centralized orchestration

It may be that the microservices pattern can only be applied to operational decision-support and behaviour profiling situations. But if that’s the case, I still see great potential in a world where many trillions of sensor-generated events will be published, consumed, filtered, aggregated, and correlated. I’m no longer a developer, but as an architect, I’m always on the look-out for patterns that could: either apply to future vendors’ products and services, or could act as a guide for in-house software development practice.

As always, I’d be keen to hear your views, examples and opinions about microservices and their potential application to the IoT. Have you come across examples of microservices pattern in an IoT context – deployed or in the labs?

I whole-heartily recommend setting aside an hour to watch the video of Fred George’s presentation on microservices:


131108 1110 Dune Fred George Recording on 2013-11-08 1106-Vimeo from Øredev Conference on Vimeo.

Post-post:
  • Another great post about microservices  – including downsides.
  • More here including “The 8 fallacies of distributed computing”.
Duke Energy are doing some interesting things in the Edge Processing space.

Here’s a video on microservices in the conext of IoT  (worth ignoring the references to Cloud/Azure):

http://www.microsoftvirtualacademy.com/training-courses/exploring-microservices-in-docker-and-microsoft-azure

I’d like to talk to anyone who’s impelmenting/ thinking about a Staged Event Driven Architecture using microservices for Edge Processing.

Phil Wills on experience of deploying microservices at The Gaurdian
2 years, 11 months ago

Architect or Coach?

Is it just me, or are others finding the Enterprise Architect role shifting towards ‘Coach/Facilitator’? 
These days I find I’m most attracted to Tweets about workshop facilitation and business analysis techniques rather than anything discussing Enterprise Architecture: frameworks, methods and tools. 
Here’s a few links I’d recommend for those interested in the former.

3 years, 2 months ago

Whole-Brained Business Analysis – New Metaphor Required

I’ve been guilty using the much debated ‘Left vs Right brain’ metaphor to explain what I believe is needed. By way of example, Alec Sharp (@alecsharp), Sally Bean  (@Cybersal), Roy Grubb  (@roygrubb) and I have been Tweeting about Concept Modeling vs Concept Mapping. Alec is keen to get Data Modelers to abstract their thinking up from physical Data Models by thinking conceptually and I have been encouraging Business Analysts to think similarly when gathering requirements. This has meant that we both find that we need to introduce a different mindset: one that encourages more creative & inclusive discussion atthe initial   discovery and play-back stage of the Requirements-Solution Design journey. I expect the Agile/XP community will declare this to be their philosophy (and nothing new) and they’re probably right. But rather than get caught-up in ‘IT-centric’ methods, I’d rather think of it as a way to better understand any requirements for change – regardless of the Software Development Life-Cycle. I’d rather see such thinking applied to all aspects of business change – people, process, practice, policy and … technology.


Tried-and-tested analytical techniques should not be abandoned, they just need to be augmented with others that, in my experience, help expand ideas and produce resilient, coherent and business-value-creating solutions.  Both side of the equation are equally important. However, I’m finding (through experiment) that the more creative techniques are more engaging – simply more fun and inclusive – and, this alone, can, in my recent experience, dramatically improve business outcomes. 

In attempts to explain the need for a more ‘whole-brained’ approach, I’ve been following the lead of the ‘Design Thinking’ community in referring to both Theory X and Theory Y from MIT Sloan and the Left-brain Right-brain metaphor. This, however, is fraught with problems due, in large part to the findings of the University of Utah who debunk such binary thinking (as I was reminded by Rob England – @theitskeptic).

So I’m in a quandary: on the one hand I find that an X-Y, Left-Right, metaphor is a simple way to convey the difference between, say, Analysis vs. Synthesis, on the other hand, however, I run the risk of aligning with outdated concepts being fundamental reconsidered by neuroscientists. 

I guess the Complexity Science community might say that I’m talking about the difference between ‘Complex Adaptive’  vs. ‘Complicated’ systems, but, again, academic debate makes coming up with a simple metaphor next to impossible.

Has anyone found an alternative metaphor for a more balanced approach to Business Analysis and Enterprise Architecture?

Importantly, I’m keen to avoid the impression that people are to be seen as fundamentally one way or another. My observation is that it is the practice of Business Analysis/Enterprise Architecture that needs to be more ‘Whole-brained’ – not the individuals per se.

To get the discussion rolling, I’d like to hear views on:
  • A good Business Analyst or Enterprise Architecture must be a balance of Left-X(Reliability – Doing-things-Right) and Right-Y (Validity – Doing-the-right-thing)
  • We’ve spent to much time of methods that attempt to industrialise EA (the TOGAF 9.0 manual runs to around 800 pages in the attempt) and BAs are too often focused on methods focus on an ‘IT solution’ rather that the Whys and Whats of the current or desired business behavior
  • We need to spend more time on developing pattern-based storytelling skills in BAs and EAs to deliver break-through changes and allow for innovation in TO-BE models.
  • Economic churn and environmental challenges warrant more Y-minded thinking (with appropriate X-controls)
  • The world can’t be fully explained or governed algorithmically (thank god!)– not while values and trust dominate the way organisations function.


 

3 years, 4 months ago

Re-purposing the Technical Debt Metaphor

Recently, I had cause to re-visit the ‘Technical Debt’ metaphor coined by Ward  Cunningham when referring to agile software development:
I am finding, however, it applies to a much broader set of circumstances such as: unmanaged introduction of Consumer-grade I.T., Line-of-Business ‘Credit -Card-Cloud’ consumption and ‘technology-solution-without-a-requirement-and/or-architecture’ implementations. So I’ve had a go a rewriting Ward’s original words:-

“Technical debt is a metaphor an incremental, get-something-started approach with the easy acquisition of money through fast loans.



A monetary loan, of course, has to be paid back with interest. In terms of software development & technology selection &  deployment, payback requires the technicians to re-work the solution as they learn more about how it interacts with other technologies and which features are being used, or not, or are now needed. Just as monetary debt can easily spiral out of control if not managed properly, so can technical debt.



In business, the metaphor is often used to illustrate the concept that an organization will end up spending more in the future by not having sufficient understanding the complete requirements before selecting a solution. The assumption is that if an organization chooses to ignore a course of action it knows should be taken, the organization will risk paying for it in terms of time, money or damage to the organization’s reputation in the future. As time goes by, efforts to go back and address the missing requirements may become more complicated and, otherwise, messy. Eventually the problem may reach a tipping point and the organization must then decide whether or not to honour its original debt and continue investing time and effort to fix the problem. This decision can be made more difficult by something called ‘the sunk cost effect’, which is the emotional tendency of humans to want to continue investing in something that clearly isn’t working (e.g. can’t scale or missing features)”.


Anything you’d add/change/delete?