Bridging the business-IT gap — how I can support your digital business
I am a tech/business consultant and developer, with experience and toolset for solution design, development, metaprogramming, data analysis, documentation, product management, product ownership, content marketing, consulting.
In this blog post, I will share the top challenges with bridging the gap between the execution of business strategy vs IT solutions I saw in my projects so far, and the way I can help you to tackle them.
A preview of upcoming attractions:
- Challenge #1: Integrate your multiparty business model ← smart contract based transaction systems
- Challenge #2: Separate the signal from the noise within the apparent paradox of seeing the AI hype and doomerism at the same time ← understanding the fundamentals, business model design
- Challenge #3: Showcasing your company’s expertise in the blogosphere ← content marketing, coaching
- Challenge #4: Without a second opinion next to your vendors’ claims and recommendations, you are flying blind ← unbiased assessment of trade-offs
- Challenge #5: POCs are not always useful ← POC design and evaluation
- Challenge #6: Finding experts for a niche, e.g. smart contract development ← metaprogramming
- Challenge #7: Not many programming languages are business friendly ← Rust
- Challenge #8: Business/legal stakeholders and IT experts don’t speak the same language ← show, don’t tell
- Challenge #9: The potential of digital collaboration tools is not fully exploited ← hacks for seamless idea/information transfer
- Challenge #10: Eliciting early feedback from business stakeholders ← demo hacks
- Challenge #11: Missing the forest for the trees with ticket management software ← solution design
Challenge #1: Integrate your multiparty business model
Nowadays more often than not, services are bundled, combining multiple service providers’ contributions. So business workflows should be composed, but implementing such composed workflows, spanning silos within and across organizations is far from being trivial.
How I can help: smart contract based transaction systems
Several platforms are on the market offering business workflow composition, labelled as “blockchain”, “DLT”, “smart contract”, “interoperability”, “distributed application platform” etc.
One of these platforms is the Daml/Canton platform, offered by Digital Asset. I’m a certified Daml developer. I’ve been working for more than two years on Daml projects in partnership with Rethink Ledgers, a blockchain consultancy and developer company.
I’m also an advocate and educator of Daml, see my latest (and so far the best) blog post about it: A Daml ledger tells a story–how does the action happen?
Besides Daml, I can help you with other blockchain platforms like Ethereum, Corda and the Corda network, Hyperledger Fabric and others.
Challenge #2: Separate the signal from the noise within the apparent paradox of seeing the AI hype and doomerism at the same time
The AI arms race kicked into overdrive recently. At the same time, AI doomerism became part of mainstream media and scientific discourse. Some products like ChatGPT and other language models offer huge benefits, and sometimes prove to be disappointingly dumb. How can you separate the signal from the noise within this whirlwind of apparently contradicting trends?
How I can help: understanding the fundamentals, business model design
This topic needs to be approached from two angles at the same time: assessing the potential of the technology, and being able to spot the business opportunities the technology provides.
I study intensively the mathematical fundamentals and practical challenges of the AI technology. I’ve completed the Deep Learning specialization by DeepLearning.AI, and I’m working towards my Tensorflow developer certification.
See my recent blog post Discovering the Transformer architecture and others in my Beneficial Intelligence collection.
I also have experience and a toolset for business strategy and business model design.
Currently I put my two cents in two trends and one missing puzzle piece:
- Trend #1: The combination of smart contract based transaction networks and AI. These two disciplines are like yin and yang. Smart contracts offer strong legal foundations for the collaboration of independent parties. AI offers effective private strategies within the limits drawn by the common frameworks.
- Trend #1: Graph neural networks, currently used e.g. to building fraud detection systems and forecasting. Large language models are dumb because they don’t have a world model. Knowledge graphs offer just that extension.
- Missing piece: Intelligibility of smart contract code. Smart contracts are already quite good at encoding rights and obligations, and the underlying transaction systems are good at enforcing these rights and obligations. What is missing is the legal prose equivalent of the smart contract code. Without this, it’s hard to speak about a “meeting of minds” which is an indispensable element of contract law. I hope that language models can help with generating the correct prose equivalent of smart contract code.
Challenge #3: Showcasing your company’s expertise in the blogosphere
Being able to express your vision and ideas about business and technology topics clearly and concisely has undeniable benefits and can even impact your bottom line.
How I can help: content marketing, mentoring
There are some business executives who are also excellent bloggers. If you are one of them, I want to learn from you. If not, maybe I can help you with either writing for your company or coaching you for better writing.
Before entering the IT industry, I worked for more than a decade as a political journalist. At the time when mobile content became a thing, initially in the form of text messages and WAP sites, I joined a telco company for writing short content, and I also became an expert of expressing ideas in a short, clear and concise way.
I am a blogger, published several blog posts on the Digital Asset blog, and did content marketing for other clients.
Challenge #4: Without a second opinion next to your vendors’ claims and recommendations, you are flying blind
If you have chosen a certain IT platform to support your business strategy, it certainly aligns with your main objectives. On the other hand, for the implementation details there are always different options with their specific trade-offs where the optimal solution for you may or may not perfectly align with your vendors’ priorities and incidental blind spots. If you don’t have in-house experts to uncover these trade-offs in an unbiased way, you are vulnerable to your vendor’s product strategy and cost-benefit expectations.
How I can help: unbiased assessment of trade-offs
I am an independent consultant so I can work with you for your best interest.
Challenge #5: POCs are not always useful
POC stands for “proof of concept”. In order for it to be useful, a POC needs to challenge some concept relevant to your project and needs to be evaluated properly.
This is theory. In real-life projects, for various reasons, sometimes demos which yield nothing else than show something that works, are passed off as POCs.
How I can help: POC design and evaluation
A POC, in order to be useful, needs to be designed so that it highlights some trade-offs important for the project, and yields material to evaluate those trade-offs from a business perspective.
Challenge #6: Finding experts for a niche, e.g. smart contract development
Example: it’s a challenge to find experts for a certain paradigm of smart contract development because it’s sometimes too “legal” for programmers and too “IT” for lawyers. I mean that smart contract paradigm which aims at expressing and enforcing rights and obligations by data recorded on a shared virtual ledger, together with computer code linked to pieces of data.
How I can help: metaprogramming
One example: a large part of a smart contract model is the implementation of a static data model. That part of the code is actually boilerplate and can be generated from any machine-readable representation of the business requirements. In this way, you can concentrate your scarce resources to the parts of the model which really matter, the implementation of the ledger updates.
Challenge #7: Not many programming languages are business friendly
In many cases, the choice of the programming language(s) used in your project is predetermined by some external factor. If this is not the case and you have freedom in choosing your language, there are at least the following factors to consider:
- Expressivity. Meaning, how you can represent high level real-life and business concepts in your data types. The highest level of expressivity in programming languages currently is the support for “algebraic data types” (ADTs). Trade-off: ADTs are supported by functional languages, but these can be too slow and memory hungry for some applications.
- Speed. There are many high-level programming languages out there but they are not famous for speed.
- Safety. Systems programming languages are fast, but some of them lack the required type safety (see null pointers), memory safety or thread safety.
How I can help: Rust
Rust is a popular programming language which is expressive, fast and safe at the same time. It borrows concepts from both functional and older systems programming languages.
The only objection against using Rust that it’s not very easy to learn, because of some novel concepts it introduced for memory management.
I am intensively learning Rust, and I can help your organization embrace it.
See my blog post about why Rust is a suitable client language for a Daml ledger: Rust + Daml: a biz-friendly smart contract platform deserves a biz-friendly client language
Challenge #8: Business/legal stakeholders and IT experts don’t speak the same language
When business stakeholders, legal experts and IT experts use the same words like “transaction”, “platform”, “service” etc. sometimes they mean different things and may not even notice it.
How I can help: show, don’t tell
During the years, I developed a natural “comparative linguistics” for the language of different communities working together in business/IT projects.
On top of reflecting on the use of language, other communication tools like diagrams, design documents and demos help a lot to establish a “ubiquitous language” (see Domain Driven Design) for the project.
Challenge #9: The potential of digital collaboration tools is not fully exploited
Digital collaboration tools potentially have the power of seamless idea and information transfer from requirements to solution design to implementation in a consistent, reproducible way. The sobering reality is often that this information flow is scattered with manual steps, the need for ad hoc interpretation and version mismatch. Excel is still the single most often used digital tool in the office, and is often used as a free-form drawing canvas recording unstructured information.
How I can help: hacks for seamless idea/information transfer
It’s not what tools you use but how you use them.
“Digital” should mean machine-readable, self-explanatory and automatically updated.
The solution can be as simple as a human-editable and machine-readable, well-structured Excel layout, extracting Miro mind maps to structured CSV, or as advanced as Jetbrain’s Meta Programming System, a platform for creating business-oriented domain specific languages.
Challenge #10: Eliciting early feedback from business stakeholders
Humans interact with your application via a UI. Such interactions are necessary from the early stages of your project for eliciting feedback from the business stakeholders. But building a full-fledged UI at the time when the overall functionality of the system is still fluid means either that you will have to rewrite your UI many times which is wasted effort or that you get trapped in a UI which doesn’t fit to the final version of your application.
How I can help: demo hacks
There are many ways to demonstrate the functionality of your system between the two bad extremes of showing incomprehensible JSONs coming back from Postman transactions and building UI too early.
Some examples are feeding filtered JSON result of API calls into Python Pandas dataframes which look nice in Google Colab or Jupyter notebooks, or using the Neo4J graph database UI to demonstrate Daml event graphs.
Challenge #11: Missing the forest for the trees with ticket management software
It’s a fulfilling experience to mark tasks completed for the individual contributors, and watch burn-down charts for people in charge for projects. This might be the reason for the undeserved popularity of ticket management software beyond its proper application domain, which is, well, ticket management.
Granted, the work won’t do itself, and projects need visibility about the meaningful units of work, about their dependencies, and about who will do them and by when. But focusing only on the “tickets” means we mistake the desired business result for the price of getting there, and give the false impression that there is a one-to-one correspondence between business requirements and implementation todo items.
How I can help: solution design
As an intermediary work between properly elicited business requirements and implementation tasks, solution design documents need to be written and kept up-to-date with the changing requirements and insights gained during implementation. This document should be the anchor place for todo items for the work to be done.
For the documentation part there are various options:
- The implementation can be as simple as having a solution design document published as a Google Docs/Sheet and personal todo items attached to the appropriate sections.
- You can use a proper product management software where the feature roadmap takes the center stage.
- Or you can even use your familiar ticket management software, with the tickets linked to a proper solution design document shared with all stakeholders.
