K.I.S.S. Keep It Simple Stupid. It was introduced to me by a legendary a Creative Director at a multi-award-winning strategic design agency. Many designers that worked there left with this phrase ‘KISS’ ingrained in their mind. Why is keeping it simple so important? Because in a land where it is ever increasing in noise, and attention span is getting smaller, keeping things simple benefits everyone. But how do you keep the sometimes messy, often siloed and mass amount of data simple?
New strategies and ways of working challenged the norm. Then slowly was integrated in and adapted and evolved. Taking on new things are difficult but changing the mindset around them can help more people adapt to the new.
Key Data Challenges
Data is the new oil. Discussed, pulled apart and reimagined since 2006 by Clive Humby. People recognized quickly that the vast amount of data being collected online due to the pandemic was a tsunami like wave that companies needed to react fast to. Marketing was jumping at the opportunity available from all the information coming in, along with other business heads wanting to see what was happening. However, many business structures or data strategies were not yet prepared for the influx that was at their door. In some industries, governance and regulators were further behind then the technology itself, holding companies back from being able to access or utilise the data to keep up with quick new tech start ups that were able to work quickly and no legacy.
Culture
Company culture is always a core challenge. Creating teams agile enough to be reactive and resourceful with the information they were receiving from the data.
Data Ownership
Finally, ownership. Who owns what? From GDPR, consumers vs. companies and differences state by state or country by country. Big changes were made to help consumers have sight of cookies and data sharing. But what about internally? Within your company, who has owned, manages, and helps with data insights and knowledge.
With so many challenges, companies are looking at ways to adopt new strategies that cover as many of these across the board – all while monitoring costs that big data is incurring. One approach is data as a product, also known as DaaP.
Data as a Product (Daap)
Taking the approach of data as a product, has many different benefits. When it comes to company culture, or building a better understanding of the data strategy, taking the DaaP approach allows people to view this mass of information differently. By looking at Data as a product, much like you would a car or drink, teams can work on strategies to get the most out of the data.
Another reason data as a product is successful across businesses is the strategy allows for easy to access information. Allowing it to become easier to consume data coming in.
‘’While an organization might have hundreds of use cases on its road map, they typically fit one of five primary consumption archetypes.’’-McKinsey
McKinsey reports that those 5 archetypes are:
- Digital applications
- Advanced analytics systems
- Reporting systems
- Discovery sandboxes
- External data-sharing systems
One of the biggest wins to this approach is that it is already showing that it saves time and money when applied correctly. However, to achieve these requires a similar application as you would with any product development. Product ownership, management, and financing. Four core points to achieve this that should be met are Dedicated management and funding, Standards and Best Practices, Performance tracking, and Quality assurance.
Making Data Rain
So far DaaP looks to help internally with a wider understanding of the use and management of Data. Opportunities to continue to harness, integrate, and utilize more data. What more could you want? Maybe to make money from the data that you have cleaned, consumed, and have as readable data. Many businesses that have utilized the Data as a Product mentality are also seeing opportunities to monetize off the hard work of making the data already catchable into consumable data, externally.
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