Productization

Insights

*Inference is a by-product/output of a data product. However, encapsulation of standalone intelligence can be considered as an inherent component of a data product. Perhaps, an analogy in the physical world could be a self-driving car with custom-algorithms to sense environment around the car.

What is Productization in Data?

Productization is about creating a deterministic "outside-in" value-based benefit. They key question here is in the interpretation of the term value and importantly, whose value here - the business or the customer. It all begins with asking the all important question, "What benefit can I offer to my customer with the data we currently own" and NOT "How can I make my data valuable for my business" or "What value does my data hold for my business". The latter refers to inside-out value generation (also known as business value generation - which is creating more inventions for our business stakeholders to push things into the market. Its like making the whole world know what you want them to consume), while the former relates to an outside-in approach (also known as customer-value generation - which is innovating for the customers. Its more akin to what they want you to make). * Note the emphasis in you v/s they.

With the conventional definition of Productization, we are simply turning raw data into "some" value-added products or services that can be sold, licensed, or used internally to improve operational efficiency. With this ideology, the market will be flooded with unwanted products and hoping that some of these products hit the customer's needs - game of chance - don't ask what happens to the products that have no demand. Monetization can never be the primary objective or outcome of Productization. There can only be but one benefit of Productization - Innovation for a cause.

Why Productization

#1

Outcome based and not Output based

Internal innovation to meet external needs Productization shifts the paradigm from an internal business value to more outward (customer) value fulfillment. There is a distinct outcome based motivation in productization. With the advent of advanced algorithms and model development, localized embedded intelligence makes productization more appealing now than ever before.

#2

Efficiency & Scalability + Consistency & Standardization

Reduced data prep processing Real-time application enabling the opportunities to increase the improved interactions with end users. Productized data can be delivered in real-time or near-real-time, making it suitable for applications that require up-to-date information for algorithmic decision-making.

#3

Integration with AI/ ML platforms

Monetization Productized data can be seamlessly integrated into various AI/ML platforms and tools, simplifying the development and deployment of machine learning models. Companies can create data products and offer them as services, generating new revenue streams by providing valuable data to other businesses or researchers.

#4

Consent & Privacy Management

When data is productized, it can be governed more effectively to ensure compliance with privacy regulations and obtain proper consent for its use.

Key Considerations for Successful Productization

  1. Data Quality: Ensure your data is accurate, complete, and consistent, as poor quality data can lead to flawed insights and decision-making.

  2. Security and Privacy: Protect sensitive information by implementing robust security measures and adhering to privacy regulations.

  3. Interoperability: Design products that integrate seamlessly with existing systems, avoiding silos and promoting fluid data exchange.

  4. User Experience: Deliver intuitive, user-friendly interfaces that facilitate easy adoption and maximize customer satisfaction.

  5. Continuous Improvement: Regularly update and refine your data products, incorporating feedback and embracing emerging technologies.

  • Repeatable

  • Standardized

  • Automated

  • Packaged

  • Standalone

  • Deterministic (in Value)

Now, lets say a customer buys 100 Glasses (various types - Beer, Wine, Cocktail etc.) for a Cocktail bar of their Restaurant. A Cocktail drink is productized at a value of 100 euros per cocktail, through the agency of:

  • Repeatable tasks, such as measuring, shaking, stirring, garnishing, straining, glassware selection, layering, rimming glasses etc.

  • Standardized procedures for each recipe, standardized measuring tools (jigger, jigger caps etc.), standardized glassware for each type of drink, standarized techniques for shaking, stirring, layering and straining, standardized garnishings such as lemon and orange slices or pierced olives etc.. Standardized locale (think of ambience, location, view, space, privacy etc.)

  • Automating tasks such as making ice cubes and crushed ice, dispensing drinks with precision and to consistent ratios, blending drinks to a uniform texture, dispensing garnishes that are finely cut and prevent wastage

  • Packaged through selection of glassware where the drink is contained that releases the standalone concoction of ingredients rendering a tasteful pleasure to the consumer.

  • The cocktail drink along with the "standard ambience" (read standardization above) is collectively standalone and does not need any other additional component, or an external ingredient, interaction or interface to render its pleasure to the consumer. In other words, all the ingredients are prepackaged in the drink or in the "standardized ambience" that's a part of the product.

  • The price and the eventual value of the Cocktail drink is fixed (deterministic) as long as the above parameters remain unchanged. This offers an element of certainty in valuing all Cocktail drink products at "this" Bar (over other services offered).

Now interestingly, let's say, the same recipe of the cocktail drink, including the exactly same glassware is offered by a street side vendor (assuming, of course, that the vendor is licensed to sell cocktails on the street) at a price of 10 euros per drink. Of course, the street-side vendor may not be able to afford the same ambience as a cocktail bar including the standardized components offerred by the bar. The street-side vendor chooses to productize in a different way, keeping the recipe of the cocktail drink exactly the same. The drink is now productized based on the custom parameters created by the vendor:

  • Repeatable tasks, such as measuring, shaking, stirring, garnishing, straining, glassware selection, layering, rimming glasses etc. The vendor masters these skills as a one-man "street-bartender" and manages to streamline repeatable tasks in their routine to produce a cocktail drink.

  • The vendor standardizes procedures, measuring tools, glassware, techniques and also garnishings, but cannot standardize a cocktail ambience, but makes up for it by standardizing fast-ordering and fastpayment standards through a mobile-app. And let's say that this app is deeply embedded in the productization of Street Cocktails.

  • The vendor can automate some tasks such as making ice cubes and crushed ice but may not be able to replicate superior automation as the cocktail bar. This lowers the efficiency, but compensates through labor personalisation (which unfortunately cannot be productized and remains within the confines of a service).

  • The vendor's cocktail drink is packaged through a selection of glassware quite in a similar manner as the bar, but without an external ambience.

  • The vendor's cocktail drink is now standalone for the consumption value it provides. The consumer does not have to depend on an additional supplement for consumption - the pleasure is fully contained in that glass of drink in their hands.

  • Deterministic Value of the Cocktail drink is fixed as long as the above parameters remain unchanged. This offers an element of certainty in valuing all Cocktail drink products at "this" Street-side vendor.

Now, moving away from drinks, a nearby shop offers custom-Kaleidoscopes for a price 5 euros per piece using the same glassware procured from the same glass factory that supplies glassware to the cocktail bar and to the street-side vendor. Customers who wish to design and build their own Kaleidoscopes can choose their glassware from a display of glassware, get the glassware colored with special paint(s) of choice, enjoy the process of breaking their chosen glassware to smaller pieces of their choice, assemble the pieces in a "kaleidoscope-maker", package the kaleidoscope to their choice of decor and have fun. Here the productization pathway has entered a new dimension using the same core product - Glass. This is to show how productization through the means of the 5-core dimensions can generate value:

  • Repeatable: are the tasks that go on to make a product repeatable (at least some of them)?

  • Standardized: can parts/ingredients/processes of the product be standardized?

  • Automated: can tasks be automated?

  • Packaged: can the product be packaged for unit consumption?

  • Standalone: does the product need an additional supplement outside its packaging during consumption?

  • Deterministic Value: does the price of the product remain fixed so long as all the attributes that go into its production remain unchanged?

In summary, productization introduces us to the concept of embedding intrinsic value within repeatable, standardizable, automated and packageable things. In the age we live in, where consumers find it increasingly difficult to evaluate the offered benefit in services, leading to de-valuing offerings on the longer run, productization offers a pathway to objectively fix economic value of a benefit. Of course, as long as they can be productized, i.e. meet the key criteria of repeatability, standardization, automation and packageability for standalone consumption and a deterministic value.

What does it mean to productize?

Let's suppose you are a glass manufacturer and have a glassworks factory where you melt raw materials, such as sand, soda ash, and limestone, and then shape, form, and process the molten glass into various types of glass products, such as bottles, drinking glasses and cups. Let's say, you have several outlets in your factory for selling finished glass products. Let's use the example of one such outlet that sells Drinking Glassware that are priced at 5 euros per piece at the factory outlet. Producing drinking glassware typically involves:

Would you like more information?

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Invoke Ingenuity Data Topology Specialist

Ingenuity Framework is designed and maintained by our Data Topology team who are backed by our R&D on TDA sciences.