USE CASE

Monetizing Models and Data Science Services

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Customers want outcomes, not data. Data is an input, but data combined with models delivers optimal results. Models enable data engineering, matching and analysis to provide specific answers, accelerate integration and reduce time to value. Next-generation data businesses deliver data science services to collaboratively develop models that deliver real-world outcomes. They then productize and monetize those models, rapidly launching them to a wider market and managing them at scale.

Harbr customers are monetizing models and data science services to reduce the time, cost, effort and skill required to achieve real-world outcomes.

Challenges

Shifting any paradigm is challenging. Adding model and service-based products to your business means overcoming a range of challenges:

1.

If you have a data business, expanding your core value proposition to include models requires a mindset and capability shift

2.

. Developing models requires close collaboration with customers to understand the nuances of the use case. Delivering data science services can enable and accelerate the collaborative development process.

3.

Slow, manual and disjointed processes to develop and productize models will make the journey from innovation to commercialization challenging. This can negatively impact margins, time to market, and the potential competitive advantage.

4.

. Thought must be given to how a model-based product will be priced during development and goto-market. Data, models and services can be priced individually, packaged or combined.

Monetizing Models and Data Science Services with Harbr

Service Delivery

Models are collaboratively built with customers, data access is fully secured, and compute and tooling are provided on-demand. All within a branded, data commerce experience that delights customers.

Service Delivery

Service Delivery

Model-based Data Products

Outputs and models created during service delivery are rapidly transformed into scalable data products and are launched selectively, or to an entire customer base, with a single click.

Model-based Data Products

Model-based Data Products

Dynamic Subscriptions

Dynamic subscription plans enable multiple customer propositions with variable pricing, legal terms and access controls that are auto-enforced

Dynamic Subscriptions

Dynamic Subscriptions

Automation

Model execution and data distribution are fully-automated on an event-driven or scheduled basis delivering high-value, high-margin customer outcomes.

Automation

Automation

If you’d like to learn more about the Harbr data commerce platform: 

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Focus Areas

From our work with next-generation data businesses across multiple industries, we have identified critical focus areas when monetizing models and data science services.

  1. Product Mindset – Data science services will only yield a scalable outcome if a product mindset is adopted at the start of every engagement. Deliberate focus on the use case, target persona, business value and wider market opportunity will provide a framework for what is required. It will also inform whether the commercial opportunity is desirable.

  2. Customer Journey – Thought must be given to what the customer journey will look like when consuming models and data science services, including quality, convenience and speed, and the associated financial costs. Knowledge of the use case, persona and business value will help to inform what is required.

  3. Market Testing – The first use of a model or the successful delivery of a data science service provides an indication of a potential market. Initial customer engagements will provide further feedback on product market fit, which is typically an iterative process.