Data Without Strategy Is Just Noise

Data-driven is something many organizations aspire to become, however too few are able to perform. As a data engineer and strategist with 15 years in the industry, I happen to see many companies spend huge budgets on hirings, costly systems and code lines, without a clear strategy, or with a lack of strategic alignment (the last was mentioned on Forbes lately as one of “10 reasons why your organization still isn’t data-driven”. 

When there’s no strategy, data projects are resulting as a standalone dashboard or automated data process, but without the structure of a common goal. It is common for businesses to set up initiatives for data analysis and usage. However, these projects are often siloed, without a central authority or leader to oversee them .As a consequence, these initiatives operate independently, generating information but lacking a shared objective. Furthermore, these initiatives may overlap, leading to duplication of efforts, wasted resources, and frustration among data scientists behind the scenes! 

Building a data strategy it’s not a privilege, but a must

‍So.. What does data strategy actually mean?
Data strategy is essentially a vision of how the organization intends to use its data, and a set of definitions for how they will go about it. Also, every business has a different data strategy. There's no set playbook on what to do exactly, but there are some guiding principles that can help you to define, plan and execute it correctly. A data strategy is, in some ways, similar to a business strategy. Just like how you set out your vision for your business, your data strategy will outline how you want to use your data to give your business a competitive edge. 

Who should be involved in the process?
‍This process requires a deep and wide understanding of your unit economy. This is why you should keep your marketing, finance and operations stakeholders in the loop - share the plans with them, collect their feedback, make sure their requirements and needs are getting appropriate response and get their buy-in and advice.

‍How to build a data strategy that works?

‍Like all good things, it is divided into three parts :)

• Step 1: define data needs The first step is to map your unit economics (customers, P&L structure, etc) and define its data needs. It also helps to make an alignment on organization language, hierarchies, and even on calculations (currency, time zone, etc.). In this stage you can enrich your org data literacy (or as we call it: "your data language").
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• Step 2: create a plan - be clear about where you want to go and what needs to happen to get there. You can start by setting your end goal and aspirations. It always helps to make a market research of trends to better understand what options are best for your org. Building a data structure requires a wide understanding of the daily use of the data - if your business org needs to have a performance metric at all business levels (from the production floor to the overall picture), you should build the data structure accordingly. 

important - Your performance metrics affect each other - understand the interrelationships and focus on the core metrics that you and your team can improve.

• Step 3: Execute, monitor and set accountability executing a strategy isn’t only about getting things done, it’s actually more about ”making room” for the new strategy and change. It always helps to   build an executive forum to get a long term organizational accountability around the strategy, develop a Data-Driven learning culture  (data literacy workshops, best practices guides and “how to” guides for all to all new processes and procedures) and of course - stick to the process and monitor it daily.

Although building and executing a data strategy sounds like a privilege that belongs to enterprises only, it appears to be more accessible than you can imagine. I believe that the next generation of products and technologies in the data world should offer a bridge between data, people and business, to help SMBs to build and execute their data strategy. 

This is why we founded our platform - Wideview. 

At Wideview you can find an all-in-one platform that enables your data strategy of growth. The platform has three models that connect, translate and visualize your data and also produce and assign related tasks and to the right positions in the org. With Wideview, data strategy never seems to be so easy and accessible!

You can read more about Wideview here

This process requires a deep and wide understanding of your unit economy. This is why you should keep your marketing, finance and operations stakeholders in the loop - share the plans with them, collect their feedback, make sure their requirements and needs are getting appropriate response and get their buy-in and advice.