From Data to ACTION (or: How to Stop Logging and Start Doing)
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From Data to ACTION (or: How to Stop Logging and Start Doing)

Tags
Data Analysis
Strategy
Actionable Insights
Published
April 2, 2024
Author
Stephanie Wiechers

From Data to ACTION: How to Stop Logging and Start Doing

In today's world, we are living in an era of data abundance. The advancement of technology has made it possible to track every minute detail, literally everything. This abundance of data is a goldmine of insights and opportunities. However, the real challenge lies not in the collection of this data, but in interpreting it and converting it into actionable insights that can drive decision-making and strategy.

The Types of Data We Have Today

Every company’s data can basically be divided into two categories: Information Technology (IT) and Operational Technology (OT). The first category provides information about general company performance and will use systems that are either general or industry-specific. The second category, OT, is very broad. In manufacturing, it involves all data logged in your machines, be it on a granular level or comprised into a MES. But even the hospitality sector will have OT, with a POS system and ticket sales!
 
The table below gives some examples of the different data sources.
Information Technology (IT)
Operational Technology (OT)
SaaS product data (CRMs like Hubspot, Salesforce)
Manufacturing Execution Systems (MES)
Accounting data (Twinfields, Exact)
Production data from separate machines through PLC
ERP system
Supervisory Control and Data Acquisition (SCADA) system
Supply chain management system
Data from digitally operated machines like a CNC, vision system, or robot
Excel sheets (project management, financial, inventory, etc)
Point of Sale (POS) data
 
Handling multiple types of data can be complex, especially when each type of data comes in different formats - the bits and bytes from your machines are different from what you wrote down in an Excel sheet. Therefore, it is crucial that all data types are translated into a common format that allows for interaction and analysis.

The Problem of Information Overload

The abundance of data can sometimes be a double-edged sword. With so much data available, decision-making can become overwhelming. This is the problem of information overload. There are common pitfalls in data interpretation that can lead to incorrect conclusions or missed opportunities. This could be due to a lack of understanding of the data, a lack of context, or simply not knowing what to look for in the data.

Tools for Data Analysis

To help with data analysis, there are several SaaS products available for tracking. These include dashboards and Business Intelligence (BI) tools. Each of these tools has its own unique features and benefits. For example, Google Analytics (and Looker Studio) has an intuitive way of working and relatively low licensing cost, Microsoft PowerBI is often used since the Microsoft cloud (Sharepoint) is already in use and it’s easy to inter-operate with company excel sheets and connect with common APIs, while Metabase offers a free, open-source dashboard solution with low cloud hosting cost and a super easy, yet flexible user interface.
Regardless the tool used, two things are important: interoperability (create the connections to all data sources) and how it is used (graphs are fun, but insights and ACTION! is what we’re looking for). Really - and this one is not fun to say - there is no point in creating nice graphs if they are not driving the right business insights. We need to make sure that we’re not only tracking, knowing what goes well. Design the business intelligence in such a way that it’s easy to see where and how to improve (on efficiency, on time, on cost-effectiveness, on operations…)

Ways to Move from Data to Action

There are several ways to move from data to action. It always involves some steps: get your data in the right format, put it into an overview (a graph, a number, slides, dashboard) and decide what the next step should be. Now, we all have the data, but we don’t have the time. We’re busy with our own work, the clients are calling us, we have our operation to manage. What to do?
(1👩‍💻) You could hire an internal data analyst. This would give you a dedicated resource for data analysis (who knows all about the company!), but it could be time-consuming to onboard, and expensive. It’s certainly the best way if you need a full-time data analyst. (2📈) Alternatively, you could learn to use the tools yourself. This gives you more control and flexibility, but it could also be time-consuming if you're not familiar with data analysis. Plus, you probably have other stuff to do. (3🎖️) Another option is to partner with an external agency. This could be a cost-effective solution that saves you loads of time and gives you access to expert knowledge and fresh perspectives.
 
Prefer to read things in list-format? I got you covered⬇️
  • Hiring an internal data analyst: Pros and cons
    • Expensive
    • Takes time to onboard
    • Full-time data analytics resource
    • You control your data
  • Learning to use the tools yourself: Pros and cons
    • Only feasible with a limited amount of data formats
    • Easy to create new overviews
    • Costs time you may not have
    • No need to onboard anyone
  • Partnering with an external agency: Pros and cons
    • Cost efficient
    • Highly knowledgeable on all tools + interpretation methods
    • Data warehouse can be set up in such a way that you can easily add new overviews yourself
    • Brings a fresh perspective

The Cost of Poor Measurement

You have the data, you know the numbers. What are you doing with it? Yes, there are basic strategies, but how do you know what to improve over time?
Poor interpretation of data can lead to missed opportunities. You may have all the data and know all the numbers, but without the right strategies for interpretation and action, you may not know how to improve over time. This could lead to stagnation and inefficiency, which could cost your business in the long run - or in most of our cases, it just costs us money and time (and energy).

Strategies for Turning Data into Action

There are several successful strategies for turning data into action. For example, data can be used to optimize staff efficiency, by matching staff numbers to actual demand over time. It can be used to identify the bottlenecks in a production process, showing where you can save time. Track financial performance throughout the company in an easy way by automating reports, showing you performance overall with availability of a deep-dive (possibility to click through for higher granularity on what sticks out).
The key is not just to provide advice, but to provide a solution space. This means providing possible actions and their expected outcomes, which allows for informed decision-making. You stay in charge - while the data saves you time. This, in turn, can lead to improved efficiency, operations, sales, and finance.

Case: Optimise Operational Staff

In the first case, data showed that operational staff efficiency could be optimised. Pearstop analysed the data and presented a set of metrics: some concerning “standard” performance metrics, and some showing anomalies and possibilities for improvement. The most striking was where we matched operational staff present, split by task, to the demand at any given moment. It quickly became clear where there was redundancy. This insight led to a redistribution of tasks which resulted in a saving of 0.5 Full Time Equivalent (FTE) in a group of 3 FTE, equating to a 17% time saving on this part of the operation.

Case: Interactive Project Planning

The second project we’ll outline here was for the project management office of a bank. Their question was: we have 23 projects in the pipeline and 21 more on the shortlist for 2024. What is feasible and how can we realise as much as possible?
We developed an interactive tool that offered a comprehensive visualisation of the “solution space”. Utilizing collected data, we were able to compare the demand (per department) from selected projects with the existing department capacity. This information was presented in a user-friendly and digestible format that allowed for efficient project selection and planning. This tool provided management with crucial insights into the feasibility of taking on projects and requirement of extra resources, considering capacity, budget, and time. It served as an effective aid in decision-making, ensuring the selection of projects was both practical and strategically sound.

Learning From The Case Studies

Instead of giving an advice (”this is what you should do”), provide the solution space. You see the possible actions and there expected outcome, so you can make an informed decision for your business.

Conclusion

The importance of moving from data collection to action cannot be overstated. By intelligently interpreting and utilizing the data available to us, businesses can improve efficiency, operations, sales, and financial performance. It's about time we stopped logging and started doing.

Looking Forward…

Some of the things we do here at Pearstop are.. putting all the data you’ve been collecting in a digestible format, so it makes it easy to see what your options are. We can give advice on how to get started yourself (just book a call, we can give you 30 minutes of our time, no worries). If you’re like most of our clients, you probably have other stuff to do. You can drop us an email with your question to see if working together would be a fit.
 
 
 

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