Data

Jo Hands is talking all about data. Every organisation has it in abundance, but not many companies have it organised and streamlined to drive meaningful outcomes. It's a shame. Data is powerful - data that has been analysed with other variables is powerful. And data can tell you the why - data can tell you why or get you to understand the trend.

Every organisation has data in abundance, but not many companies have it organised and streamlined to drive meaningful outcomes.  It's a shame…

Data is powerful

Data that has been analysed with other variables is powerful. 

Data can tell you the Why

Data can tell you why or get you to understand the trend.

Data can drive the predictive analytics

Data can give you the 'so what' or now that we know 'what can we do with this information' .

 

Data should drive:

  • Strategy decisions 

  • Operational decisions 

  • Pivot on strategy 

  • Operational improvement 

  • Good commercial decisions 

 

At Whiteark we are big on data. We use data and data tools to analyse a problem / or root cause and we use data to drive value creation and measure success. 

We have a number of case studies at Whiteark that demonstrate the power of data and what we have achieved with our clients.

Data is powerful. If you need help to generate the power, reach out to Whiteark.

Browse more articles about the power of data: 


Need support in your organisation? Reach out.

Whiteark is not your average consulting firm, we have first-hand experience in delivering transformation programs for private equity and other organisations with a focus on people just as much as financial outcomes.

We understand that execution is the hardest part, and so we roll our sleeves up and work with you to ensure we can deliver the required outcomes for the business. Our co-founders have a combined experience of over 50 years’ working as Executives in organisations delivering outcomes for shareholders. Reach out for a no obligation conversation on how we can help you. Contact us on whiteark@whiteark.com.au


Article by Jo Hands, Co-Founder Whiteark

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Big Data, Business Strategy, Data Whiteark Big Data, Business Strategy, Data Whiteark

The Importance of Data Visualisation

Here at Whiteark, we love data, it’s at the centre of everything we do, it gives us that facts, and in order to interpret what the data is telling us, and communicating our findings with key stakeholders, data visualisation plays a fundamental role.

Here at Whiteark, we love data, it’s at the centre of everything we do, it gives us that facts, and in order to interpret what the data is telling us, and communicating our findings with key stakeholders, data visualisation plays a fundamental role.

What is Data Visualization?

In today’s business environment, and the rise of big data upon us, we need to be able to interpret increasingly larger batches of data. Data visualization takes the raw data, models it, and delivers the data so that conclusions can be reached - it provides visual context of what the data/information means through the use of maps, graphs, tables, infographics or other visual formats. This makes data more natural for the human mind to comprehend and makes it easier to identify trends, patterns, and outliers within large data sets.

Users of Data Visualisation

Data visualisation is used across all industries to improve top line and bottom-line growth across all aspects of the organisation. As a crucial step in data analytics, data visualisation enables companies to unleash the power of their data by highlighting critical insights and messages that would otherwise be lost.

Benefits of Data Visualisation

The key benefit of data visualisation is the positive affect it has on a company’s decision making process – it enables businesses to recognise patterns more easily and faster. Below are some specific ways that companies can benefit from data visualisations:

Understanding Trends:

Analysing current and historical data allows companies to understand trends over a period - where they were and predict where they can potentially go. Applying data visualisation to this type of application is one of the most valuable.

Identifying Frequency:

Frequency is related to Trends Over Time but refers to the rate of particular instances/occurrences – i.e., understanding the frequency of customer purchases and at which point in the customer journey they make their purchase supports companies with predicting/planning different marketing and acquisition strategies for potential new customers.

Recognising Relationships:

Data visualisation simplifies identifying the correlations between the relationship of independent variables – this allows companies to make more informed/better business decisions.

Examining the Market:

Data visualization takes the information from different markets to give you insights into which audiences to focus your attention on and which ones to avoid. We get a clearer picture of the opportunities within those markets by displaying this data in visual representation.

Performance:

The ability to obtain real time information with data displayed clearly on a functional dashboard allows companies to act and respond swiftly. It helps leaders identify challenges/ areas for improvement and provokes decisions to pivot more quickly.

Assessing Risk and Reward:

Analysing value and risk metrics requires expertise because, without data visualization, we must interpret complicated spreadsheets and numbers. Once information is visualized, we can then pinpoint areas that may or may not require action.

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Data Visualisation Techniques

There are a range of methods that can be used to distil data/information in a way that can be visualised. It’s important to understand the type of data being modelled and what its intended purpose is, before determining the most appropriate visual representation. Some visualisations are manually created, while others are automated. Below are some examples:

Infographics: infographics take an extensive collection of information and give you a comprehensive depiction. An infographic is excellent for exploring complex and highly subjective topics.

Heatmap: This is a graph with numerical data points highlighted in light, warm and dark colours to indicate whether the data is high-value or low-value.

Area chart: This chart is great for visualising the data’s time-series relationship.

Histogram: Histograms are used for measuring frequencies. These graphs show the distribution of numerical data using an automated data visualisation formula to display a range of values that can be easily interpreted.

Overall, data visualisation is important tool in today’s environment as it summarises a plethora of information in a way that makes it easier to identify patterns and trends, rather than looking through thousands of rows on a spreadsheet. The purpose of data analysis is to gain insights, and data is much more valuable when it is visualised as it simplifies communicating the findings to a broad range of audience groups.

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