4 Stages of the Data Cycle: How Home Workers can use the data cycle to improve their job and work

4 Data Cycle Stages and how Home Workers can use Data to Improve your productivity and work

Introduction

Understanding the Data Cycle will help you improve the work you do and the projects you undertake.

The Data Cycle can help home workers to improve their working efforts, by giving them a framework to judge their key performance indicators and metrics, take action and make improvements (as needed).

After you have read this article you should have a greater understanding of the data cycle and how to use it within your business.

How to use the Data Cycle as a Home Worker

The Data Cycle has four stages: Plan > Do > Check > Act.

Below we will discuss and highlight each of these stages. In more detail and then highlight an example project. We are going to use Marketing as an example for this article, however, the Data Cycle can be used in all lines of work and business.

Stage 1 - Plan

This is the most important phase as you are setting the groundwork within the Data Cycle. At the planning stage, you are looking to understand how data drives your business goals. If you do not have a strong handle on the relationship between the data and your business goals, you will end up making the wrong decisions.

Spending the time now, to ensure that you are tracking and collating the correct date is going to pay real dividends later on.

There are two fundamental questions to ask yourself:

1. What are your marketing and/or business goals?
2. What data would demonstrate progress (or lack of) towards those goals?

Answering these two questions will help you shape the Do, Check, and Act stages.

Stage 2 - Do

This stage is all about data collection. Data collection is a fancy way of saying what has happened to a particular metric. A metric can be anything from click-through rate to sales calls made. The important thing to remember in this stage is that the data you want to collect should be coll-collectable time-sensitive format.

For example, recipients' options in an email marketing campaign are hard to track, however, you can track the numbers who clicked on links or opened the emails.

Now you do not always need fancy software to be collecting this data, a spreadsheet that is updated daily with just two columns can suffice, It all depends on the answers from the planning stage.

How will I collect this data?

How often will I collect this data?

Where will I store this data?

How will we ensure this is done regularly?

Who will be responsible?

Who will I be reporting the data to?

What decisions will I be making from this data?

Remember the data needs to be relevant to your goals and time-sensitive.

Stage 3 - Check

This stage is all about checking the results of the data. Looking at what has happened understanding what it means, and understanding what actions you might have to take in the action phase.

This is what is called in some circles Data Analysis, Data Analytics, or Data Science. Those terms have a habit of being used interchangeably in the popular business press (that is the topic for a whole other article).

It can be a complex process or a very simple process depending on what data you have collected. However, there are three questions to ask yourself in the check phase of our business goals.

1. Have we reached our marketing goals or defined metrics e.g. sales presentations per week?
2. If we have not reached our metric do we understand why? e.g. Did we send enough marketing emails?
3. If we have reached our metric what can we do to improve further? What has worked so far?

Stage 4 - Act

The Act stage is all about taking action based on what the data has revealed in the check phase.

It requires a thorough examination in the check phase and then planning out and taking action based on what the data says. The amount of action will depend on your marketing goals, activities, etc.d it can include the action of keeping things as they are.

Questions you need to ask

1. Do we continue as we are, based on the data in the check phase?
2. Things have not gone well, what actions do we need to test to see improvement? If so what actions do we need to take and complete by when?
3. Things have gone well and are on track, do we take additional or different actions in an attempt to improve our results? If so what actions do we need to take and complete by when?
4. Can we test the changes before rolling out the full scale? If so what actions do we need to take and complete by when?

The specifics of the Act phase are very much dependent on what has happened in the check phase and what data was collected.

EXAMPLE

Plan:

Your marketing goal might be to increase the size of your email list by 1,000 subscribers in the next 100 days as you have identified that email list size is a key driver of acquiring new customers.

As have a goal - of 1,000 extra subscribers and a data point to track total email subscribers.

1,000 subscribers across 100 days is ten subscribers a day.

You decide that you are going to build the email list through Facebook advertising campaigns and a landing page.

Do:

You undertake your marketing efforts, notably on this occasion using Facebook advertising.

You use Facebook to direct traffic to a newsletter landing page.

Every day you record the number of new email subscribers in a simple two-column spreadsheet (date & and new subscribers).

Check:

Every Monday you check the results to ensure that the campaign is on track. In week one, the campaign is not on track. You are only getting 5 subscribers, not 10.

Looking at the data you see that the conversation rate is a third lower than expected.

Act:

You decide to increase the advertising rate by 33% to test whether this will help you reach your goals.

You return to the planning phase of the data cycle reconfirm your goals and then follow the steps above and find a week later that it has had the desired result.

Actionable Project

This is a simple project that will test the Data Cycle across two weeks.

In this project in week one, you are going to send a specific number of client pitch emails via face-to-face, telephone, or team meetins.

You are going to test the best headline for these emails. Use the Data Cycle above to test and implement this process over two weeks with weekly check-ins.

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This article is an extract from the forthcoming book Recruitment Agency Marketing Toolkit soon to be found on Amazon and all good bookshops.

Please do let us know the results of your test by emailing me at?[email protected]

TL;DR

• The Data Cycle is an analytical tool that can be used to assess marketing activities.
• The Data Cycle is in 4 stages Plan>Do>Check>Act
• Each step has an important part to play in using data effectively.
• The Data Cycle process can sometimes be called Data Analysis, Data Analytics and Data Science by people as the terms can be misused.
• The Data Cycle allows you to run simple and effective marketing experiments.