Scale Your Start-Up by Refining Your Data Strategy – TDWI
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Once you are ready for accelerated growth, continuing with the same data strategies can hold back your start-up.
When your start-up is at the brink of scaling, it is tempting to do more of what’s already working. However, continuing with the same data strategy that helped you come this far will actually hold you back from the exponential growth you want. During the early stage, a start-up’s data strategy prioritizes validation of the business model, refinement of the value proposition, and establishment of product-market fit. This strategy will no longer serve a start-up that is ready to prioritize expansion and optimization. Although this sounds right in theory, many start-ups continue using the strategies they’ve long outgrown in practice.
For Further Reading:
The Most Effective Enterprise Data Analytics Strategies Always Look Beyond Technology
How Pyramid Thinking Can Revolutionize Your Data Strategy
Must-Know Data Strategy Priorities for CIOs
Where an Early-Stage Start-Up’s Data Strategy Falls Short
Let’s say a healthcare technology start-up making wearable fitness trackers spent its first two years collecting usage metrics directly from its product such as steps taken, heart rate, and sleep patterns. They used this data, quite successfully, to tweak and refine both their product and messaging which led to increased user adoption, engagement, and retention.
Delighted with their success, the start-up decides it’s ready to go global and distributes their wearable in new continents, but soon they find that their adoption, engagement, and retention rates begin to decline. Worse still, the same metrics decline in their origin country.
The plan was that once they expanded into new markets, they would continue improving the product to fit the needs of the new users based on the same data and that this continuous improvement would keep attracting and engaging users the way it did before. This process had worked, so “why fix what isn’t broken?” Unfortunately:
In with the New: The Growth-Stage Start-Up’s Data Strategy
Many start-ups experience the same story, not realizing that the answer lies in upgrading their data strategy to fit the realities and complexities of achieving greater scale. Yet many start-ups continue to use the strategies that were made to succeed in the early stage. The following data strategy will help you if your start-up is about to enter the growth stage, a stage where maximizing time, money, and efficiency is key.
Expand Your Data Infrastructure
Prepare for a massive surge in the volume, velocity, and variety of data by investing in tools that can comfortably process large amounts now and in the future. If you are using a manual input process, replace it with an automatic one, and expand the number of tracked metrics to encompass scaling-specific business goals, particularly those of revenue generation.
To simplify the use of this updated infrastructure, you must also create a single reference point that allows you to access all your data from one place because during the scaling phase, you will need to cut down on time and effort spent searching for data and spend more time actually leading with insights. According to McKinsey, 19% of working hours are spent searching for information. That number may be much higher in growth-stage start-ups due to the absence of a fully established data infrastructure in such businesses. Therefore, for your start-up’s data strategy to operate at its highest potential, having this point of reference will unlock more time to find insights at a pace that can keep up with rapid scaling.
Invest in a Strong Data Culture
Start-ups in the growth stage often prioritize hiring product managers and marketing professionals. Build more features. Attract more customers. Data analysts are then hired to help these people track their work. Great. However, in the absence of a strong data culture that’s bent on value creation without hierarchy, these analysts simply pull data, clean it up, and deliver unactionable reports. According to Gartner, lack of data culture is one of the top reasons why only 20% of insights provide actual business outcomes. A framework that can streamline the creation of insights that lead to profitable outcomes can be very useful here.
View all | Become a contributor
Register today to attend this TDWI Webinar and be the first to hear the latest TDWI research into current trends, challenges, and solutions for reducing time to insight and taking advantage of real-time data. 03/25/2024
Register today to learn how your organization can benefit by unifying cybersecurity and data infrastructure with a modern security data lake and security ETLs. 03/26/2024
This TDWI Expert Panel webinar explores the opportunities and challenges for data democratization, focusing on the tools, technologies, and organizational strategies that can facilitate democratization. 03/27/2024
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This article was autogenerated from a news feed from CDO TIMES selected high quality news and research sources. There was no editorial review conducted beyond that by CDO TIMES staff. Need help with any of the topics in our articles? Schedule your free CDO TIMES Tech Navigator call today to stay ahead of the curve and gain insider advantages to propel your business!
Once you are ready for accelerated growth, continuing with the same data strategies can hold back your start-up.
When your start-up is at the brink of scaling, it is tempting to do more of what’s already working. However, continuing with the same data strategy that helped you come this far will actually hold you back from the exponential growth you want. During the early stage, a start-up’s data strategy prioritizes validation of the business model, refinement of the value proposition, and establishment of product-market fit. This strategy will no longer serve a start-up that is ready to prioritize expansion and optimization. Although this sounds right in theory, many start-ups continue using the strategies they’ve long outgrown in practice.
For Further Reading:
The Most Effective Enterprise Data Analytics Strategies Always Look Beyond Technology
How Pyramid Thinking Can Revolutionize Your Data Strategy
Must-Know Data Strategy Priorities for CIOs
Where an Early-Stage Start-Up’s Data Strategy Falls Short
Let’s say a healthcare technology start-up making wearable fitness trackers spent its first two years collecting usage metrics directly from its product such as steps taken, heart rate, and sleep patterns. They used this data, quite successfully, to tweak and refine both their product and messaging which led to increased user adoption, engagement, and retention.
Delighted with their success, the start-up decides it’s ready to go global and distributes their wearable in new continents, but soon they find that their adoption, engagement, and retention rates begin to decline. Worse still, the same metrics decline in their origin country.
The plan was that once they expanded into new markets, they would continue improving the product to fit the needs of the new users based on the same data and that this continuous improvement would keep attracting and engaging users the way it did before. This process had worked, so “why fix what isn’t broken?” Unfortunately:
In with the New: The Growth-Stage Start-Up’s Data Strategy
Many start-ups experience the same story, not realizing that the answer lies in upgrading their data strategy to fit the realities and complexities of achieving greater scale. Yet many start-ups continue to use the strategies that were made to succeed in the early stage. The following data strategy will help you if your start-up is about to enter the growth stage, a stage where maximizing time, money, and efficiency is key.
Expand Your Data Infrastructure
Prepare for a massive surge in the volume, velocity, and variety of data by investing in tools that can comfortably process large amounts now and in the future. If you are using a manual input process, replace it with an automatic one, and expand the number of tracked metrics to encompass scaling-specific business goals, particularly those of revenue generation.
To simplify the use of this updated infrastructure, you must also create a single reference point that allows you to access all your data from one place because during the scaling phase, you will need to cut down on time and effort spent searching for data and spend more time actually leading with insights. According to McKinsey, 19% of working hours are spent searching for information. That number may be much higher in growth-stage start-ups due to the absence of a fully established data infrastructure in such businesses. Therefore, for your start-up’s data strategy to operate at its highest potential, having this point of reference will unlock more time to find insights at a pace that can keep up with rapid scaling.
Invest in a Strong Data Culture
Start-ups in the growth stage often prioritize hiring product managers and marketing professionals. Build more features. Attract more customers. Data analysts are then hired to help these people track their work. Great. However, in the absence of a strong data culture that’s bent on value creation without hierarchy, these analysts simply pull data, clean it up, and deliver unactionable reports. According to Gartner, lack of data culture is one of the top reasons why only 20% of insights provide actual business outcomes. A framework that can streamline the creation of insights that lead to profitable outcomes can be very useful here.
View all | Become a contributor
Register today to attend this TDWI Webinar and be the first to hear the latest TDWI research into current trends, challenges, and solutions for reducing time to insight and taking advantage of real-time data. 03/25/2024
Register today to learn how your organization can benefit by unifying cybersecurity and data infrastructure with a modern security data lake and security ETLs. 03/26/2024
This TDWI Expert Panel webinar explores the opportunities and challenges for data democratization, focusing on the tools, technologies, and organizational strategies that can facilitate democratization. 03/27/2024
View All >>
TDWI Members have access to exclusive research reports, publications, communities and training.
Individual, Student, and Team memberships available.
Membership Information
Privacy Policy Cookie Policy Terms of Use CA: Do Not Sell My Personal Info © 2024 TDWI
All Rights Reserved
This article was autogenerated from a news feed from CDO TIMES selected high quality news and research sources. There was no editorial review conducted beyond that by CDO TIMES staff. Need help with any of the topics in our articles? Schedule your free CDO TIMES Tech Navigator call today to stay ahead of the curve and gain insider advantages to propel your business!
