Why you need a Data Innovation Strategy

Essential building blocks for creating a workable data strategy.

Data Innovation Strategy?

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.


1). Lack of data strategy?

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.

2) Lack of a data audit for data innovation?

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.

3). Nakala Data Strategy Approach

In Nakala Analytics, we have adopted a unique cost effective way to help you jumpstart your data innovation journey. Our essential building blocks for creating a workable data strategy demands that we give each & every business unit a chance to think through the past and envisage the future. This activity involves a detailed data collection process which seeks to understand the current positioning of the business as well as the needs of the organization. Following an environmental scan and a thorough data audit, SWOT Analysis will be used as a tool to evaluate internal and external influences which are dependent on data and its effects towards supporting the overall mission and vision of the company now and in future. This analysis shall be carried out as the third activity of this project. In this analysis, we provide a systemic picture of the present state of data utilization, identify opportunities for business growth as well as gain insight into the extent to which the systems analyzed are ready to embrace a data driven working environment. In addition, the analysis will also provide critical risk factors as well as a risk aversion matrix that will aid in the implementation of the data strategy. To implement the data strategy, a broad range of efforts which focus on the transformation of strategic intentions into action shall be undertaken. This simply resonates around communication, interpretation, adoption, and enactment of our strategic plan which will involve taking data driven ideas, decisions, plans, policies, objectives and other aspects and implementing them into action.

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