All our projects benefit from our team expertise applied to a multiplier of how well we are able to make breakthroughs for our customers. By paying attention to the process we are able to minimize inefficiencies and gradually make consistent decisions that will be conducive to improvement multiplying breakthroughs.
Approaching digital products using the metrics necessary to make the right calls now, and in the future requires background work on details that could easily get overlooked.
The metrics should be measurable and/or representable as an already existing external or internal source:
The first stages of the consultation are onboarding meetings with two phases: Phase 1 – the pitch where we create your statement of work or proposal for approval; Phase 2 – the design procurement where we finalize the properties to be used in design, development and launch. After the onboarding, there will be different consultation meetings depending on the source of the offer. Basically, the meetings will debrief and align our communication for working as a capable unit. Keeping us nimble and proactive so that we can address business initiative threats without fail.
Focusing on human-centered design means that we don’t assume who the most capable party to answer questions about the digital product and data transformation. Building up to that “aha!” moment could be customers, materially-involved stakeholders or management. Often this person, or group is hidden behind stacks of unanswered questions or unapproachable problems. Research allows us to apply methods of rigorous discovery breaking-down barriers to progress. Research comes into play early during design, and can continue for the life of the digital product which makes data transformation important. A quick tip is that later research can be used internally to validate against the metrics we chose in onboarding phase.
As the delivery date approaches, we will generate documentation that can be used to guide updates, and future data transformations. Research will be included in this document for a robust log of key points that will increase internal stakeholder and customer adoption.
Development can be many things in terms of data transformation and digital products:
The results from research may require adjustments during the development phase that will allow the solution to successfully pass final acceptance tests. Since these adjustments based on research can be anticipated they offer the highest cost/value implementation ratio.
What has a unknown cost/value implementation ratio is when new requirements are introduced during development, and this happens quite often. To make this probability less problematic towards meeting deadlines is near impossible. Ideally, if we effectively leverage research introducing progress-slowing design changes during development will not happen because high cost/value ratio features will win over low ratio features.
Digital products as a data transformation dictates that launching the product will create new opportunities in the future and mitigate threats to the business.
Data transformation done right always opens up new horizons in data-driven insights. Internal organizational culture has to be built around having data at your fingertips.
To use a digital product as the typical case study for data transformation. After launch the product will enter the introduction phase of the product lifecycle. One of the things that happens at this point is that marketing steps in to grow the customer base. Then comes growth and maturity phases. The final stage is the decline stage which can be replaced by a product extension stage. Data transformation applied during the other stages will build an accurate resource to use for choosing how to extend the life. Marketing data will give an idea of when this stage should start, and tying in financial reports, customer feedback, usage data, customer service data, and other key metrics will pay dividends beyond any strictly delineated boundaries.