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The Value of Data Science for Business

How the power of data can (should) create tangible business value

This is the first article in a 2-part series!!

Organisational Data Science

Few would argue against the importance of data in today’s highly competitive corporate world. The techniques used to transform this data into actionable insights are crucial to the performance of an organisation. A study carried out by McKinsey & Company reported that companies that lean on their customer analytics are 23 times more likely to outperform competitors in acquiring new users and 19 times more likely to achieve above-average profitability than their non-data-driven competitors.

However, the reality is that data is worth very little if you don’t have highly skilled professionals who can derive actionable insights from it. Knowledge is what drives business value, and data science is the process through which this knowledge is created. Being able to harness the power of data science is thus extremely valuable.

The problem is that the advantages that could be captured by having an effective data team in place remain elusive to many organisations around the world, meaning that these businesses will continue to amass large amounts of data with no fundamental understanding of how to use it.

The reality is that data science is about giving data a purpose — and this is the job of your data team.

Mission statement

The prevailing missions of any data team is to 1) create insights from data and 2) communicate those insights to the relevant stakeholders across the business. Within these united missions exist three basic functions that are fulfilled:

  • Decision making: Across any organisation, people need to make impactful decisions. The data team creates or empowers the rest of the business to use their results that make these data-informed decisions possible.
  • Objective setting: Having an effective data team in place means your organisation is on its way to quantifying all measures of success and failure. In doing so, all business objectives become measurable.
  • Monitoring: The data team, together with other business agents, define key indicators at all levels of the business, which are continuously monitored, analysed, and reported on for identifying new opportunities and issues that may arise.

Business value creation

Now that we know the business goals and functions of the data team, it’s time to consider the value they can bring to the organisation. Below are just some of the many different ways data science can provide actionable business value.

1. Empower business agents

By generating otherwise hidden insights from a company’s data, the data team can guide non-technical business agents across the organisation, in different departments, to make better-informed decisions, thus optimising potential outcomes.

2. Help achieve business goals

The data team can guide the upper management levels and the C-level executive team with their analytics to help devise business strategy in critical divisions, including the revenue drivers — marketing and sales — to ultimately improve all business operations and increase profitability.

3. Create a more data-informed culture

An effective data team shows everyone how data can be leveraged to generate actionable insights. By doing so they 1) encourage all teams to contribute to greater business value by making more data-informed business decisions, and 2) help the upper echelons of the organisation better understand and appreciate the advantages of data science & and its wide-scale adoption.

4. Drive experimentation & idea creation

Companies are constantly experimenting with company data and creating models using this data that simulate a variety of potential actions to show which path is expected to bring the best business outcomes.

They can also test the decisions made based on these models to see how they have effected business operations, to measure key metrics that are related to important changes and quantify their success.

5. Identify new opportunities

The job of the data team requires them to continuously and constantly improve the value that is derived from the organisation’s data. They are continuously looking for new opportunities for improvement and developing new methods of analysis, making it possible to discover new revenue streams.

6. Save costs and losses

No longer do businesses need to take risks or make uneducated guesses about what will work. Instead, they can make decisions based on quantifiable, reliable data insights. Data science allows you to understand business operations on a whole another level.

From modelling the business cost of retention to analysing workforce turnover, to evaluating management and overhead expenses, data teams can help their companies identify cost-saving opportunities that can potentially improve business functions & increase profitability.

7. Gain competitive edge

A fundamental goal of a firm is to develop and maintain a competitive advantage in the market. But how are these advantages created and maintained in dynamic competitive environments? By identifying (and seizing upon) these market opportunities and outmanoeuvring perceived threats.

All of the answers to unlocking this ability lie in company and market data that, when analysed, allows you to garner insights that drive business value, thus marginalising competitors.

 

Are Companies Leveraging This Created Value?

This brings us to the crux of the discussion — whether or not companies are really leveraging these different types of value created by data teams to help achieve business goals, identify new opportunities & stay ahead of the curve.

To answer this question, one must consider the crucial difference between value creation and value extraction. Any business can employ an effective data team with all the required positions filled by domain experts. And this team can be ingesting, processing, and analysing terabytes of data to generate and report on new & exciting insights (value creation).

But if these insights are not being effectively communicated to the right audiences around the organisation & thus are not being applied by the various business agents (value extraction), then what is the point in the first place?

How to truly leverage the value created by your data team will be the focus of our next article — stay tuned!

 

Title Photo by Annie Spratt on Unsplash

Kyle O'Shea
Kyle O'Shea
With a strong background in economics, Kyle started his career in financial analytics. He now heads up the Kyso Community and our internal data science team. He likes to visualize data that help us to better understand economic and social inequality issues.

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