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Digital Transformation Services

Digital transformation is the phrase most likely to precede a stalled project, because it is usually sold as a governance structure and a big-bang rewrite. We treat it as engineering: the systems that do not talk to each other, the data that disagrees with itself, and the manual work people do every day to paper over both.

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What Digital Transformation means in practice

Who it’s for: Organisations where the friction is spread across several systems and the process joining them, and where the business cannot pause while that is put right.

Ask ten organisations what digital transformation means and you will get ten answers, most of them about culture. Look at what is actually wrong and the answer is far more specific. Someone re-keys the same order into two systems because they were bought six years apart and never introduced. The finance team maintains a spreadsheet that is really a database, because the software cannot produce the view the business needs. Three systems hold a customer record and none of them agrees on the address. A process that should take a morning takes a week because it stops four times to wait for a human to move information between two screens. None of that is a culture problem. It is an integration problem, a data problem and a process problem, and those can be engineered.

So the first thing we do is refuse the abstraction. We map the operating process as it is genuinely performed, which always includes the shadow layer nobody put in the systems diagram: the spreadsheets, the shared inbox that functions as a workflow queue, the report someone rebuilds by hand every Monday, the workaround invented three years ago that is now load-bearing. That map is the whole basis of the work, because you cannot sequence change across an estate you have only described at the level of logos on a slide. From there the programme becomes a list of specific, arguable engineering decisions: what to integrate, what to automate, what to replace, what to retire and, importantly, what to leave alone.

We are also willing to tell you that you do not need a transformation programme. If your problem is one ageing system that is dangerous to change, you need a legacy migration, which is a different service and a much narrower piece of work. If the cloud bill is unexplainable, you need cloud engineering. If you need two integrations and a decent report, buy those, not a programme with a steering committee attached. Transformation earns its name only when the problems are genuinely spread across several systems and the process connecting them, and when fixing one in isolation would just move the queue somewhere else.

What you get

  • A current-state map of how the business actually operates, systems, interfaces, data and the manual steps between them, including the spreadsheets and shared inboxes that no architecture diagram admits to
  • A named list of the manual bridges: every point where a person moves, retypes or reconciles information because two systems will not do it, with the cost of each one measured in the way your business already counts work
  • An integration architecture that says how systems will exchange information from now on, which system owns which data, and what happens when one of them is unavailable
  • A sequenced roadmap where each phase delivers something usable on its own and reduces the risk of the next, rather than a plan whose value all arrives at the end
  • Baseline measurements taken before any change, so improvement is demonstrated against the old numbers rather than asserted in a closing deck
  • Working software delivered throughout: integrations, automated workflows, reporting and replacements built and put into production in phases, not designed for a future programme to build
  • A written record of the decisions and their reasoning, so the next team understands why the estate is shaped this way instead of rediscovering it

What Digital Transformation does for you

  • Capacity released from work nobody wanted to do

    The manual layer between systems is invisible on any budget line, because it is not a licence or a project, it is a share of many people’s days. It shows up instead as a team that is always slightly behind, a backlog that grows whenever someone is on leave, and errors that appear at the point of transcription. Removing it produces hours back in the parts of the organisation that were spending them on being a data bus, which is usually the most durable return in the whole programme.

  • Decisions made on data instead of on recollection

    When information is split across systems that disagree, reporting becomes an act of reconstruction, and reconstruction is slow, contested and quietly discouraging. People stop asking questions they know will take a fortnight to answer. Once the systems exchange information properly and each kind of record has an owner, an ordinary operational question becomes something anyone can retrieve. The change in behaviour is bigger than the change in technology: teams start asking more questions because asking has become cheap.

  • The estate stops accreting complexity

    Nobody deliberately builds an unmanageable estate. They add one point-to-point integration at a time, each entirely reasonable on the day, until every system is wired to every other and no change can be made without tracing a dozen threads. A transformation done properly leaves behind a rule for how systems connect and a place where that connection lives, which turns the next integration into a small piece of work rather than another strand in the web. That value is paid out over years, in projects that turn out cheaper than expected.

Why teams choose us for Digital Transformation

  • You want the programme run by people who write the software, so the plan is constrained by what can actually be built rather than by what fits on a slide.
  • You want someone who will map the shadow layer of spreadsheets and inboxes honestly, because a plan that ignores how the work is really done will be routed around by the people doing it.
  • You want value delivered in phases you can stop after, not a multi-year commitment whose return is entirely in the final quarter.
  • You want to be told which parts of your estate are fine, and to have the scope argued down when the smaller piece of work would solve the problem.

What Digital Transformation includes

The concrete pieces of work this covers, scoped to what your problem actually needs.

  • Current-state and process discovery

    We establish what exists and what actually happens, which are two different investigations. The systems side covers the applications in use, including the ones a department bought without telling anyone, the interfaces between them, where each kind of data is created and copied, and what each costs to run and license. The process side is observational: we follow real cases from start to finish and record every point where the work waits, moves between systems by hand, or gets corrected. The output is a map of the operating model as performed rather than as documented, with the friction marked on it. It is frequently the first time an organisation has seen its own process end to end on one page.

  • Integration architecture and the connective layer

    The default failure mode of an estate is point-to-point: each connection built directly between two systems, in whatever style suited that week, until nobody can change anything without breaking something else. We replace that with a deliberate pattern. Every system exposes a stable interface, the connective layer handles translation between the different vocabularies systems use for the same concept, and integrations are built to survive the other side being down, retrying safely without duplicating work. Where the exchange is genuinely event-shaped, something happened and several systems care, we use messaging rather than a chain of synchronous calls that fails whenever any link does. The point is not a fashionable topology, it is that the next integration is a day of work instead of an archaeology project.

  • Master data and record ownership

    The question of which system owns the customer sounds administrative and is one of the most consequential decisions in the programme. Without an answer, every system holds a partial copy, updates flow in both directions, conflicts are resolved by whoever saved last, and reporting is permanently contested. So we settle ownership per data domain: one system of record for each, with the others consuming and not silently amending it, plus identifier mapping to reconcile records that already exist in several places under different keys. We also do the unglamorous half, the deduplication and cleansing nobody wants to fund, because integrating dirty data faithfully propagates the mess at speed.

  • Workflow automation, and where we advise against it

    Once systems can exchange information, whole steps of a process can be removed rather than merely accelerated: work routed automatically, approvals raised with the right context attached, documents generated and filed, exceptions escalated to a person only when a person is genuinely required. That last qualifier matters, because the aim is not to automate every human out of the process but to stop consuming judgement on tasks that need none. We are deliberately cautious about screen-scraping robotic automation, which imitates a user clicking through an interface. It demonstrates well and is brittle by construction, since it breaks whenever the interface changes and leaves you maintaining a robot instead of fixing the missing integration. Defensible as a temporary measure against a system with no API and a known retirement date. As a strategy it is a liability with a licence fee.

  • Reporting, and the layer where decisions get made

    A reporting problem is nearly always a data problem wearing a different hat, which is why buying a dashboard tool before the underlying records agree produces expensive disagreement rendered in colour. We work the other way round: get ownership and integration right, then build reporting on top with the definitions written down, so that when two people say active customer they mean the same thing. We pay particular attention to the questions asked every week and to the period close, because a close that takes a fortnight is almost always a set of manual reconciliations compensating for systems that do not agree.

  • Portfolio decisions: build, buy, integrate or retire

    A transformation is partly a series of decisions about software you already pay for. For each significant system we ask whether it still earns its place, whether the process was bent around it for reasons that no longer hold, and whether a supported product would do the job better than the custom thing built when nothing suitable existed. Sometimes the answer is to buy: an accounting package or a payroll system is not where a business should spend its engineering budget. Sometimes it is to build, because the process is genuinely how the organisation competes and a product would force it into a shape costing more than the licence saves. And sometimes it is to retire something quietly, the cheapest improvement available and the one most often skipped because nobody is quite sure who still uses it.

Where it fits

  • The order that gets typed in twice

    A business where sales is captured in one system and fulfilment and invoicing happen in another, with a person in the middle who re-enters each order and, once a week, works out why the two do not tally. The engineering fix is unremarkable: agree the canonical record, integrate the two with idempotent handling so a retry cannot duplicate an order, and make the reconciliation an automated check rather than a human ritual. A whole category of error stops occurring, and the organisation usually discovers the person in the middle was absorbing several other problems nobody had recorded.

  • The organisation with several versions of its customers

    A company whose customer exists in a sales system, a support tool, a billing platform and at least one spreadsheet, with no shared identifier and no agreement on which is authoritative. Support cannot see what was sold, billing chases people who already paid, and any question about revenue by customer requires manual assembly. We establish the system of record, build the identifier mapping, deduplicate what exists, and put in one-way flows so amendments happen in one place. Unglamorous, and it changes the tone of an organisation more than most things we do, because arguments about whose numbers are correct simply stop.

  • The period close that consumes a fortnight

    A finance function whose month end is a sequence of exports, spreadsheet manipulations and reconciliations, each existing because two systems disagree in a specific and well-understood way. We trace each reconciliation back to the disagreement causing it and fix the cause rather than automating the workaround, which is the distinction that decides whether the close gets genuinely shorter or merely faster to perform. What is left is fewer manual steps, an audit trail that stands up to questioning, and a finance team that gets its month back.

  • The programme that produced documents rather than software

    An organisation partway into a transformation that has produced a target operating model, a capability map, a governance framework and very little running code, where the original problems are all still present and the appetite to fund another year is gone. We convert what is salvageable into an engineering plan: identify the two or three changes that deliver most of the practical benefit, build those, and let the rest of the framework fall away. The hard part is organisational rather than technical, because someone has to be willing to say the previous plan was larger than the problem.

How we approach Digital Transformation

We start by watching the work rather than by interviewing about it, because the description of a process and the performance of it are rarely the same document. Sitting with the people who do the job surfaces the parts that never reach a requirements workshop: the field everyone knows to ignore, the second system opened alongside the first, the export to a spreadsheet that happens because the report was never quite right, the approval that is really a message to a colleague. Those details are where the actual cost is, and they are also where the cheapest wins hide, because a great deal of daily friction turns out to be one missing integration or one absent field rather than anything structural.

Then we sequence, and this is the part that separates a programme that lands from one that gets cancelled in its second year. We look for the workstream that removes real pain quickly, is small enough to finish, and leaves the estate in a better shape for whatever comes next. That work goes first, in production, in front of users, so the business gets a return early and the programme earns the credibility it needs to keep going. Everything after it is planned but not frozen, because a roadmap written in month one and defended in month eighteen is usually being defended against evidence. We revise it as the map improves, and we say so plainly when a planned phase has stopped being worth doing.

How a transformation engagement runs

It begins with a paid discovery, and we are direct that it is a real engagement rather than a free proposal with a survey attached. Over that period we inventory the systems, follow real work end to end, interview the people who perform the process and the people who receive its output, quantify the manual effort, and establish what the organisation is actually trying to achieve underneath the language of transformation. Frequently the stated goal and the real one differ: the brief says modernise the platform, the underlying pressure is that a large customer wants information the business cannot currently produce. Discovery ends in a written current state, a prioritised set of opportunities with the reasoning attached, and a recommendation, which sometimes is that the programme should be much smaller than the one you asked us to scope.

Next we do the sequencing properly, in the open, with the trade-offs visible. Each candidate workstream is assessed on the benefit it delivers, the risk it carries, what it unblocks and how long it takes to reach production. Dependencies are made explicit, because the common cause of a stalled programme is discovering in month nine that the valuable work was waiting on a data problem nobody scheduled. We choose a first phase that is genuinely useful on its own, and we take baseline measurements before it starts, since the credibility of everything afterwards depends on being able to show the before as well as the after.

Then we build, in phases, with each one going into production and being used before the next begins. That cadence is not a preference but the entire risk strategy: a programme delivering working software every few weeks can be stopped, redirected or reduced at any point without losing what has already been gained, while a programme delivering at the end can only be cancelled. Change management runs alongside rather than after, because a process improvement people do not adopt is not an improvement. Handover is deliberate: documentation of the integration architecture and data ownership, runbooks for the automated processes, the decision record explaining why the estate is shaped this way, and time with your team on the parts they will now run.

What a well-connected estate looks like

Each kind of information has one system that owns it, and the others consume rather than quietly maintain their own version. That single rule eliminates most of the reconciliation work an organisation performs, because two systems only need reconciling when both are allowed to be right. Ownership is decided per data domain and written down, and where a second system genuinely needs to hold a copy, the direction of flow is explicit and one way.

Systems connect through a deliberate layer rather than directly to each other. What that layer is depends on scale and complexity, and we are not doctrinaire about it: for a modest estate it can be a small integration service and a set of well-defined interfaces, while a larger one benefits from a message broker and an API gateway. What matters is the property, not the product. Adding a new system means connecting it to one place rather than to everything, and the vocabulary translation between systems happens somewhere identifiable instead of being scattered through a dozen scripts.

The exchanges themselves are built for the real world, in which the other side is sometimes down. That means asynchronous where it can be, with retries that are safe to repeat because operations are idempotent, and a queue for messages that cannot be delivered yet so nothing is silently lost. It also means each integration is observable: you can see what flowed, what failed and what is waiting, without asking an engineer to check a log. Most integration horror stories are not about the happy path, they are about failures that stayed invisible until a customer noticed.

And the estate keeps a boundary between the systems that run the business and the layer that answers questions about it. Operational systems are shaped for transactions, reporting is shaped for analysis, and pointing heavy queries at production is how a reporting request takes down order capture on a busy afternoon.

What changes when information starts moving

Connecting systems that were previously isolated changes the risk profile, and it deserves saying plainly rather than being discovered later. Data that lived in one place now travels, copies land in an integration layer and a reporting store, and a credential that once let a system talk to nothing now lets it talk to several. So integration credentials are scoped to the specific operations they need, held in a managed secret store rather than in configuration files, rotated, and issued per integration so that one compromise does not become general access. Transport is encrypted, and information at rest in the connective layer is treated with the same seriousness as in the systems it came from.

Under UK GDPR the questions arrive with the first integration, and they are easier to answer at design time than in a data protection assessment written afterwards. Does the receiving system have a lawful basis for the personal data now flowing to it. Is the field being sent because it is needed or because it happened to be in the payload, which is where data minimisation is most often quietly lost. Where does the data physically reside once it is copied, and does that answer still satisfy the commitments made to customers. How does a deletion request propagate to the copies. We design for these rather than retrofit them, and we keep personal data out of reporting stores where an aggregate or a pseudonymous key would serve the purpose.

Automated processes also need an audit trail a person can follow. When a workflow moves work, approves something within a threshold or generates a document, there should be a durable record of what happened, on what input and under which rule, plus an authorisation model that distinguishes what a system may do alone from what requires a human. That is partly operational, since debugging an automated process without a record is guesswork, and partly governance, because auditors reasonably want to know how a decision was reached when no person made it. Deeper security work, threat modelling, penetration testing or formal compliance readiness, sits with our cybersecurity service rather than being implied by this one.

Signs it’s time

  • People spend a meaningful part of every day moving information between systems by hand, and everyone has stopped noticing because it is simply how the job works
  • The same entity, a customer, an order, a product, exists in several systems with different identifiers and no agreement on which one is right
  • Answering an ordinary question about the business requires someone to assemble it from exports, so the answer arrives late and nobody fully trusts it
  • Processes stop repeatedly to wait for a person, not because judgement is needed but because no system hands the work to the next one
  • A previous transformation produced a target operating model, a governance structure and very little working software, and the original problems are all still there

Phased, measured, and smaller than you were quoted

We do not accept the big-bang, and the reason is empirical rather than stylistic. A programme that delivers everything at once concentrates all the risk on one date, keeps its value invisible until then, and has no mechanism for learning that a design assumption was wrong except a launch that goes badly. A phased programme puts working software in front of users repeatedly, which surfaces the wrong assumptions while they are still cheap, and leaves you free to stop at any point having kept everything delivered so far. That optionality is worth more than the theoretical efficiency of doing it all together, which in our experience never materialises anyway.

We measure before we start, because otherwise success becomes a matter of assertion. Before a workstream begins we establish the current numbers in terms the business already uses: how long the process takes, how many times information is entered manually, how often an exception occurs, how long the close runs, how long the question takes to answer. Those numbers are not marketing, they are the mechanism by which you can tell whether the next phase deserves funding. We would rather be held to a measured comparison than to a well-written summary.

And we will argue the scope down. Consultancies are paid by the size of the programme, which is a bad incentive to hand someone who is also defining what the programme should contain. Our position is that most organisations we speak to need two or three well-chosen pieces of engineering rather than a transformation, and that the phrase itself often survives only because it is easier to get budget approved for a transformation than for three integrations and a data cleanup. If the smaller version is the right answer, we will tell you, and we accept that this sometimes ends the conversation. The alternative is being paid to build something we know is larger than the problem, which is how the term acquired its reputation in the first place.

Technologies we build it with

Chosen per problem, not per fashion. This is the stack we most often reach for on this work.

How we deliver

  1. 01

    Discover

    We map the system, the constraints and the business it serves, including the parts nobody documented.

    Architecture brief

  2. 02

    Architect

    Decisions get made, written down and defended before a line of production code exists.

    Decision records

  3. 03

    Build

    Short cycles against working software. You see progress in the product, not in a status deck.

    Shipping increments

  4. 04

    Operate

    Monitoring, incident response and iteration. The system is alive, so the engagement is too.

    Runbooks & SLOs

Want a straight answer on Digital Transformation?

A short call with a senior engineer, before you write a brief. If Digital Transformation is the wrong answer for your situation, we will say so and tell you what we think is right.

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What changes

  • The manual bridges removed

    The re-keying, the reconciliation and the copy between screens engineered away one at a time, so the effort is recovered permanently rather than absorbed by hiring.

  • One version of the truth

    Clear ownership of each kind of data, with the other systems consuming it, so the business stops arguing about which report is correct before it can discuss what the report says.

  • Change that lands in stages

    Value delivered in phases that each stand alone, so the operation keeps running and no single launch is carrying the whole programme.

Industries we serve

Domain knowledge changes what gets built. A few of the sectors we know before the first meeting.

How pricing works

  • A paid discovery first, always. It produces the current-state map, the quantified friction, the prioritised opportunities and a recommendation, and it is deliberately structured so that its value does not depend on you hiring us for what comes next. Anyone willing to scope a transformation programme without doing this is guessing, and the guess will be resolved later at your expense.
  • Fixed-scope engagements for defined workstreams once discovery has established what is really there. An integration between two named systems, a data ownership and deduplication piece, an automated process replacing a specific manual one, a reporting layer with agreed definitions. Each is priced on its own and each delivers something usable, so the programme is a series of decisions you keep making rather than one you made at the start.
  • A monthly senior engagement where the work is genuinely continuous, which is common on a multi-phase programme, giving you a consistent team that keeps the context between phases instead of re-learning your estate each time. It suits organisations that want ongoing capacity without permanent headcount, and it is the shape that keeps a roadmap moving rather than restarting.
  • Third-party costs stay yours. Integration platform licences, cloud services, message brokers, reporting tools and any software we recommend are bought on your own accounts, billed to you directly at the vendor’s prices with no margin added by us. We will tell you when a paid product genuinely earns its cost and when an open component does the same job, and we do not receive anything for the recommendation either way.

Typical timeline

  1. 01

    Discovery

    A few weeks inventorying systems, following real work end to end, quantifying the manual effort and establishing what the business is actually trying to achieve. Ends in a written current state, prioritised opportunities and a recommendation that may be smaller than the brief.

  2. 02

    Sequencing and baseline

    Workstreams assessed on benefit, risk, dependency and time to production, then ordered so that early work is useful on its own and unblocks what follows. Baseline measurements taken before anything changes, so later improvement is demonstrated rather than claimed.

  3. 03

    Phased delivery

    Integrations, data ownership work, automated processes and reporting built and put into production in sequence, each in use before the next begins, with adoption handled alongside the build rather than announced after it.

  4. 04

    Consolidation and handover

    Retirement of what the new arrangement has made redundant, documentation of the integration architecture and data ownership, runbooks for the automated processes, and time with your team so they can run and extend it without us.

What working with us actually means

  • Engineers, not a programme office

    The people who map your estate are the people who then build the integrations, so the plan is limited by what can actually be delivered. There is no handover from a strategy team to an implementation team, which is where a great deal of transformation value is traditionally lost.

  • We will tell you the programme is too big

    Most organisations need a few well-chosen pieces of engineering rather than a transformation. We would rather scope the smaller thing and be right about it than accept a larger budget for work we know exceeds the problem in front of us.

  • Measured against your own baseline

    We take the before numbers in terms your business already uses, and report against them. It makes each phase auditable on its own merits, and it means the decision to fund the next one rests on evidence instead of momentum.

  • Nothing you have to keep paying us to run

    The integrations, the automation and the documentation live in your repositories and run in your accounts. There is no proprietary middleware of ours in the path, so ending the engagement means we stop working, not that something has to be untangled.

How to engage us

Three ways to work with us on this, chosen to fit the problem, not our margin.

Services in this practice

The specific services that make up this practice.

Related terms

Weighing the options

The decisions people are usually making at the same time as this one.

Common questions

How is this different from your legacy application migration service?

They solve different shapes of problem and it is worth being precise, because buying the wrong one wastes real money. Legacy migration is depth on a single system: an application the business depends on that has become dangerous to change, where the work is to stabilise it, put a safety net around it and replace it incrementally without stopping the business. Digital transformation is breadth across the estate and the process that connects it: the systems may each be perfectly healthy in isolation while the way they fit together forces people to do work by hand. You can have one problem without the other. An organisation with modern systems and no integration between them needs this page, not that one. An organisation with a single unsupported system doing everything needs that one, not this. When both are true, the migration usually becomes one workstream inside the wider programme, and we would say so during discovery rather than selling you two engagements.

Is digital transformation not just a consultancy word for expensive slides?

It has certainly earned that reputation, and we will not defend the version that deserves it: the one that produces a target operating model, a capability map and a governance framework, and leaves the organisation with the same manual processes it started with. The reason that pattern persists is a structural incentive, since a firm paid for a programme of work has every reason to define a large one. Our version is judged differently. If, at the end of a phase, your people are not doing measurably less manual work, or an answer that took days does not now take minutes, then it did not achieve anything regardless of what the documentation says. That is why we baseline the numbers before we start and report against them. If you are being pitched a transformation with no working software in the first few months, ask what specifically will be in production and by when, and treat a vague answer as the answer.

How do we know whether we actually need this?

A rough test: count the number of times a day someone in your organisation moves information from one system to another by hand, and ask how many of your recurring problems disappear if two named systems simply agreed with each other. If the answer is most of them, you do not need a transformation programme, you need those two systems integrated, and you should buy that as a piece of work rather than as a programme. If instead the friction is genuinely distributed, if fixing one system just moves the queue somewhere else, if nobody can say which system owns the customer, and if the recurring operational questions all require manual assembly, then the problems are connected and treating them separately will produce a series of local fixes that do not add up. That is when the wider shape is justified. Discovery exists to answer this question honestly, and it is a small enough commitment that it is a reasonable way to find out you do not need the larger one.

What about low-code platforms and robotic process automation?

Both have a legitimate place and both are oversold. Low-code and workflow tools are genuinely good for internal forms, approval routing and administrative processes where the logic is simple and stable, and using one can be considerably cheaper than a custom build. They become expensive where the logic gets complex, where the platform’s assumptions stop matching yours, and where you discover that the work lives in a proprietary environment you cannot test, version or migrate in any ordinary way. Robotic automation that drives a user interface is a narrower case still. It works, it demonstrates beautifully, and it is fragile by construction, because it depends on the screen not changing. We will recommend it as a bridge over a system with no API and a known retirement date, and we will advise against it as a strategy, because you end up maintaining a robot rather than fixing the missing interface underneath it.

What do you need from us for this to work?

Two things, and neither of them is a large time commitment. First, access to the people who actually perform the process, not only to the managers who describe it. An hour spent watching someone do the job reveals more than a day of workshops, and it is the only reliable way to find the workarounds that make the current process function. Second, and this is the one that determines whether a programme succeeds, a person on your side with the authority to decide. Transformation work generates questions that cross departmental boundaries, which system owns the customer being the classic example, and those questions cannot be resolved by engineers. If every cross-team decision has to wait for a monthly committee, delivery will run at the speed of that committee no matter how good the engineering is. We would rather agree that arrangement at the start than discover it in month four.

Will this disrupt the business while it is happening?

The technical disruption is deliberately kept small, because we deliver in phases and each one is scoped to something that can be put into production and reversed if it misbehaves. There is no date on which everything changes at once, which is precisely the failure mode of the big-bang approach. The honest caveat is about people rather than systems. Any change to how work is done requires the people doing it to learn something and, more importantly, to believe it is an improvement, and a process change that is announced rather than shaped with them will be quietly routed around. So we involve the people who will use the thing while their input can still change it, we pilot with a small group before rolling out, and we keep the old path available during transition where that is practical. The organisations where this goes badly are almost always the ones where the new process was designed for people rather than with them.

Thinking about Digital Transformation?

Tell us the problem in your own words, not in requirements. A senior engineer reads it and comes back with a straight view on whether Digital Transformation is the right answer here, or what would be.

  1. 01A senior engineer reads it. Not a form queue, and not an account manager.
  2. 02We reply either with questions or with a straight answer that we are not the right fit.
  3. 03If it looks like a fit, a technical call with the person who would actually run the delivery.
  4. 04Then scope, effort and risk in writing, before anyone signs anything.
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