The Digital Asset Value Model, explained

Digital assets rarely fail in a way anyone can point at. They drift. The interface stops matching how people now expect to be treated, the platform accumulates a decade of decisions nobody would make again, the data piles up without ever informing anything, and the strategy that justified the whole thing quietly stops being true. Every one of those is survivable on its own; together they produce the asset everybody has met, the one that works, costs a fortune to keep working, and returns a little less each year while the invoices stay the same.

The reason it is so hard to fix is that each team is right. Design is right that the experience is dated, engineering is right that the platform needs work, the data team is right that nothing is instrumented, and the executive is right that none of it ties to a decision anyone can defend. What is missing is not insight, it is a shared language and a common scale, so the conversation can move from whose problem is biggest to where the next spend actually pays. That is what the Digital Asset Value Model is for, and it now has a home of its own at davm.io.

Four dimensions

The model takes the four forces that decide what a digital asset is worth and treats them as equals, which is already an argument: most organisations carry a house bias, and it is usually visible in the org chart long before it shows up in the product.

• Experience - how people perceive, interact with and feel about the asset. Not the visual layer alone, but whether the thing is intelligible and worth coming back to.
• Technology - the systems, platforms and code that decide what the asset can do and how reliably it does it. This is the dimension that quietly sets everyone else's ceiling.
• Data - how the asset collects, processes and uses information, which is the difference between a product that learns and one that merely runs.
• Strategy - clarity of purpose, market positioning and decision-making discipline. The least tangible of the four, and the one that most often explains the other three.

Ten intersections, because value lives in the overlaps

Scoring the four circles on their own would tell you very little, because almost nothing valuable happens inside a single one. A beautiful interface over an unreliable platform is a liability rather than an experience, and data nobody has connected to a decision is a storage cost. So the model measures the overlaps, six of them where two dimensions meet:

• Experience and Technology, Interactive Product Quality: whether what was designed is what actually ships and performs.
• Experience and Data, Personalisation and User Intelligence: whether the asset knows anything about the person using it, and does something useful with that.
• Experience and Strategy, Customer Journey and Brand Alignment: whether the journey someone actually takes is the one the business says it wants.
• Technology and Data, Data Engineering and System Intelligence: whether information moves between systems on its own, or a human ferries it in a spreadsheet.
• Technology and Strategy, Platform Architecture and Digital Roadmap: whether the architecture can carry the plan, or the plan quietly bends around the architecture.
• Data and Strategy, Business Intelligence and Evidence-Based Decisions: whether decisions cite evidence or seniority.

Then four more where three dimensions meet at once, which is where the genuinely valuable and genuinely difficult work sits: Intelligent Products (experience, technology and data), Digital Transformation (experience, technology and strategy), Customer Intelligence (experience, data and strategy) and Operational Infrastructure (technology, data and strategy). Ten intersections in all, and most of them are somebody's job that nobody owns.

How it gets scored

Each intersection is assessed through structured statements scored one to five, which sounds bureaucratic until you have watched a room try to agree on whether the platform is fine. Statements force the argument to be specific, and specific disagreements are the productive kind: two people scoring the same statement three apart have found something worth an hour, and they usually find it in the first ten minutes.

Those statement scores roll up into intersection scores, and the intersections into the four dimension scores. The arithmetic matters less than the direction of travel, which is bottom-up: a dimension score is the consequence of specific observations rather than a general impression, so when somebody challenges it, there is something concrete to point at.

The centre score, and why your weakest dimension sets it

Here is the rule that makes the model worth using rather than merely interesting. Your centre score is your lowest dimension. Not the average, not the total, not the flattering composite that lets a strong quarter in one area cover a bad decade in another: the minimum sets the ceiling, because the centre is defined as the state where all four hold at once, and all four cannot hold at once while one of them is on the floor.

The centre is not perfection. It is the level all four dimensions can sustain together.

The consequence is uncomfortable in a useful way. Investing further in your strongest dimension does not move your score, and usually does not move your returns either, which is the arithmetic behind the redesign that changed nothing because the platform underneath it could never deliver what the design promised. The next investment belongs to the lowest number, however unglamorous that dimension is, and however recently you spent money on the highest one.

Reading the index

The result is a Digital Asset Value Index, and it lands in one of five bands:

• 1.0 to 1.9, Critical - fundamental deficiencies, where the honest response is a rebuild conversation rather than a roadmap.
• 2.0 to 2.9, At Risk - significant weaknesses that are already costing you, whether or not anyone has attributed the cost.
• 3.0 to 3.4, Baseline - adequate and undifferentiated. It works; nobody chooses you because of it.
• 3.5 to 4.4, Healthy - performing well, with specific gaps worth closing deliberately.
• 4.5 to 5.0, Leading - strong, balanced capability, which is where the compounding actually starts.

The band is not a grade and it is not the deliverable. Its job is to make the position discussable by people who did not run the assessment, which is what turns a diagnostic into a budget conversation instead of another document.

Four shapes you will recognise

Once you have four dimension scores, the shape they make tells you more than the number they average to, and in practice they make one of four:

A balanced profile is the one to want, because progress lifts everything together instead of waiting on a laggard. A spiked profile has one or two dimensions doing the work while the others quietly cap them. A cliff is three respectable scores and one that falls away, the easiest of the four to act on and the most frequently ignored, since the three good numbers make an excellent slide. An inverted profile is a single strength surrounded by weakness, which in our experience is usually a strong engineering team that nobody has told what the thing is for.

Using it

You can score your own asset in about five minutes on davm.io, and the value of doing it alone first is that you get an unpoliticised baseline before anybody has an opinion about the result. Then have two or three colleagues from different functions take it separately and compare: where your scores diverge is where your organisation does not agree about what it owns, which is worth knowing before you spend anything.

At estate scale the same instrument answers a bigger question, which is not how good is this asset but which of these deserves the next rand. We assessed 49 digital properties across five divisions for Old Mutual using a custom fork of the model, and used the results to align thirty stakeholders behind a sequenced roadmap; the method is written up in the case study.

The V&A Waterfront is the clearest case we have of the centre score earning its keep, because the answer was not the one anyone wanted. Read across the four dimensions, the precinct's estate was capped by data: the experience was decent, the technology was serviceable, and none of that mattered while the estate could not recognise a person across two properties or report one number that meant the same thing twice. Two years of work went where the model pointed rather than where the enthusiasm was, and the programme is written up in full.

When the diagnosis turns into work, it sits inside our digital transformation practice: score the estate, rank it, fix the lowest dimension on the asset that matters most, then score it again. Boards recognise that shape of conversation immediately, because it is how they already think about every other asset they own, which is rather the point of giving digital assets a model of their own.