What’s a data strategy ?
We hear a lot about datas, and especially on “ Strategy “, which comes really often when people speak about data. In this article we are going back to fundamental principles, and share what a data strategy should deliver.
First of all what is a strategy, we find more or less the same definitions within dictionary, Wikipedia describes a wrap up of official sources on this topic :
“ Strategy generally involves setting goals and priorities, determining actions to achieve the goals, and mobilizing resources to execute the actions. “
Winston Churchill said “ However beautiful the strategy, you should occasionally look at the results. “
It is so important to define what the strategy should reach, what goal should be done.
If we go back on data Strategy, what do you want to change? What do you want to reach? For example, below several examples:
Within these decisions 70% should be done from structured data and KPI.
in this case, you will probably find kind of strategies, and because everyone thinks its strategy is the best, you will have to converge on a common one representing a better ensemble.
- Aligning to the corporate strategy, on the mid-term plan, your business plan, you can deviate your business strategy in goal for your data strategy
- Increase your market share by 30% in Asia
- Increase B2C sells to 30%
- Increase EBITDA by 15%
- optimize your customer centric approach by optimizing your supply chain
- Reduce the risk from your organization (bank, insurance, but also industry will define this kind of objectives)
Depending on these general ideas, you deviate your data strategy via axles or work stream we are going to detailed below. The diagram below describes the overall approach, everything is link to each other, and pretty mandatory.
you should develop all workstream, in parallel or step by step :
- Organization
Organization means « Target operating model », so all responsibilities, teams, department, roles you should define to lead data within the full enterprise, and being successful.
Business Processes linked, or dependent to data should be identified, the data strategy doesn’t describe processes, it identify where you should focus.
- Technology
This is where you use technology, digital or not, it is important to define a technological framework, which will enable you to evaluate trends, and opportunity.
- People
one the most important, if you want to lead data literacy. Do you need to recruit? Upskill? Reskilling?
Data is a complex area, and you need specialist, but not only, the data literacy should be developed thanks to non-specialist as well.
- Business
How to align business and data topics?
How to deviate the business strategy or a general objective to concrete use case?
- Data
What data do you need?
How to structure you data?
This article doesn’t describe the « how to », I will write another one describing the step-by-step approach, if you react on it ! feel free to propose and interact with me on this topic.
Business Processes linked, or dependent to data should be identified, the data strategy doesn’t describe processes, it identify where you should focus.
This is where you use technology, digital or not, it is important to define a technological framework, which will enable you to evaluate trends, and opportunity.
one the most important, if you want to lead data literacy. Do you need to recruit? Upskill? Reskilling?
Data is a complex area, and you need specialist, but not only, the data literacy should be developed thanks to non-specialist as well.
How to align business and data topics?
How to deviate the business strategy or a general objective to concrete use case?
What data do you need?
How to structure you data?
This article doesn’t describe the “ how to “, I will write another one describing the step-by-step approach, if you react on it ! feel free to propose and interact with me on this topic.
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Originally published at https://www.linkedin.com.
