With the emerging wave of information driven technology, businesses have inevitably found themselves unable to resist technological indulgences. To keep up with trends, the industry has had to continually review its best strategies; developing solutions that address customer needs and leverage the benefits of different channels. The growth of the industry has seen inventions in utilization of big data which is helping to drive digital transformation and exploit available as well as new sources of data from both inside and outside the organization.

In a report released by Gartner in 2017, an estimated 60% of big data projects fail. While that may be true, our own investigations have found out that 90% of all data analytics projects fail. Majority of the successful ones take long to realise ROI. But why is that so. In this article, I will share with you two main reasons that lead to failure and how to avert.

A data strategy is a set of guidelines that direct investment in data assets, created to help an organization reach a specific business goal. The main reason why data projects fail is because there is no coherent road map to follow when investing in data driven opportunities and running data driven operations. The consequences of not having one business strategy can be severe starting from confusion to wrong hiring. Not having a data strategy essentially means the following:

1. The objectives that warrant investment in data innovation strategy are not solid.
2. Lack of proper understanding of data needs
3. No road map for data collection, data processing and data utilization.
4. Wrong allocation of corporate resources.
5. Wrongly matched talent and recruitment needs and approach.
6. Loosely tied perspectives (financial, customer, process, learning & growth vs investment goals).
7. Wrong culture and approach.
8. Lack of a proper plan to guide and measure analytical operations.
9. Failure by some teams to make use of data systems.
10. Incoherent communication and unclear organizational structure in data management operations.

Creation of a good data strategy requires creation-to-follow-through of a comprehensive data assessment process which studies the existing innovation ecosystem and creates an ideal roadmap bespoke to the organizations current and future market positioning.

The deliverable will present a report which maps strategic pillars to data initiatives, creating a clear roadmap of tools, products, services and people for future growth and profitability. The secret of investing in a data strategy even before recruitment is to ensure:

• You can communicate data initiatives effectively.
• Align the day-to-day data analytics work that everyone is doing with strategy.
• Prioritize analytics projects, products, and services.
• Measure and monitor progress towards strategic targets contributed by data initiatives.

This is so far the most important stage before a business invests in a data project. A data audit for data innovation is a process which seeks to provide recommendations that facilitate realistic collection, processing, usage, securing, transmission and storage of data in a manner that supports affluent innovation and attainment of expected ROI. To perform a data audit for data science means being able to:

1. Review all existing data and data sources (both primary and secondary).
2. Match strategic objectives with data assets available.
3. Identify gaps in the data ecosystem that may prevent the organization from achieving its strategic objectives and recommending way forward.
4. Identify additional innovation avenues that the organization has not thought about also called the “Data Rich & Reach”.
5. Assess data collection tools and data pipelines.
6. Assess organization wide data storage and protection needs.
7. Assess data collection points, identify gaps and recommend corrective measures hitherto.

To jumpstart your data innovation journey and realize a profitable venture, seek to create a data strategy which works hand in hand with a data audit for data innovation. The data innovation strategy will create an ideal roadmap bespoke to your organizations current and future market positioning. The deliverable will present a report which maps strategic pillars to profitable initiatives, creating a clear roadmap on products, services and data innovation for future growth and profitability.

To be sure of your data investment, the data audit will identify content and structural gaps in the data ecosystem that may prevent the organization from achieving its strategic objectives. The deliverables will consist of a detailed report with recommendations and adjustments in readiness for data innovation.