Why Dashboards are Failing, and Why Data Storytelling is the Answer

Or how to spend less time explaining to your colleagues what's happening, over and over again. 

A dashboard denotes a data visualization solution used predominantly for data analysis. It helps curate inclusive data analysis, enables users to tailor the information they want to be displayed, and provides the ideal way of sharing the analysis outcomes with other team members. 

They come with interactive features, for instance, filters to combine charts, graphs, and reports that content creators can use to project overviews. However, they're subject to failures and shortcomings like any other business initiative.


Image by Author, Information Dashboard

It's no wonder they're increasingly becoming outdated, prompting businesses to turn to data storytelling. Here's why:

The Case against Dashboards

They're set up without a user in mind

Most often, their setup occurs without the user in mind. You find that they're either complex to set up, needing assistance from an IT expert, developer, or a reporting tool that features pre-loaded dashboards that don't gauge metrics that are pertinent for all users. 

Once setup occurs without a user in mind, this can be challenging from the onset because certain software is meant for experienced developers, making them complex to set up by anyone outside the IT field. 

Dashboards are developed on a set of assumptions and priorities regarding what's important. Oftentimes, a consultant or design expert defines those priorities without familiarizing with the company. At times, the priorities might be the default measurements offered by the dashboard software. 

In most cases, businesses end up with official-looking data that doesn't support business priorities. All features of a dashboard must be important and relevant. If the choice of information that needs inclusion in the dashboard occurs without the input of those in the business context, it's unlikely that the dashboard will be maximally beneficial.

Interfacing and Compatibility Issues

Data isn't universal, so compatibility and connectivity remain a challenge among dashboards. If a dashboard fails to connect with a crucial business system, the information it offers will be outdated, incorrect, or restricted in its efficiency. To bridge this gap, users must input data manually, which defeats the goal of the dashboard.

Cost and Scalability

Dashboards can be expensive based on the provider's prerequisites and the business's size. Some providers need a license for each person who will be accessing the dashboard while others charge annual or monthly subscription charges that scale per the business size. 

Although this challenge isn't inherent, researching the cost of each dashboard and establishing its ROI is a significant step in finding the appropriate software. 

Reporting Requires Meaningful Metrics

A dashboard should measure something important. Consequently, it needs an understanding of the appropriate metric choices to display. Bear in mind that broad metrics won't offer much insight. Instead, specific metrics that affect broader ones will. 

Chart Junk. Edward Tufte, The Visual Display of Quantitative Information (1983, 2001),

Poor Presentation of Data

To serve their role and meet their potential, dashboards should display a dense range of information in a limited amount of space in a way that communicates immediately and clearly. 

This needs a design that leverages and taps into the power of visual perception and the brain to perceive and process numerous chunks of information fast. This can only occur when dashboards' visual design is central to the development procedure. 

Technology can't accomplish this. Rather, it needs somebody with design expertise. Although dashboards are distinct in numerous useful and thrilling ways, few present data effectively. 

The Case for Data Storytelling

Data storytelling takes data and combines it with a narrative to create data stories. This process converts information into stories anybody can read, comprehend, and share. The stories typically present a clear and concise message regarding what you should know about your business on a particular day. Here's why data storytelling offers a solution.

Metrics become Actionable Insights

Data storytelling empowers businesses to use significant metrics by converting them into actionable and beneficial insights while presenting them in the form of stories. It examines the key performance indicators or KPIs that align with their fundamental business objectives and converts quantitative information into result-driven narratives. 

Enhance Engagement and Communication

Oftentimes, companies face a difficult time trying to sustain an engaging conversation with their stakeholders and clients for an extended period. The key to excellent engagement and communication isn't just restricted to compiling all the data into a presentation. Rather, communication should be conveyed in an engaging manner that's easy to understand. 

Data storytelling allows companies to gather and examine data and present insight in the form of easy-to-understand and engaging visuals and narratives. This way, companies can demonstrate the worth of their services and forge a lasting relationship with their stakeholders and clients.

Image by Author: Graphite Note Notebook

Enhance Processes with Plotting

Data stories feature a definite plot with a well-constructed introduction, end, and middle. Data storytelling templates, tools, and platforms have pre-set formats and themes, which alter the visualization and story depending on the input data while ensuring the message is expressed most efficiently. 

Businesses can delineate the plot and develop a framework by considering the primary objective of the data-driven report or story and aligning it with their overall organizational goals and strategy. 

Populating the plot with relevant KPIs and visualizations can help businesses enhance the efficiency and productivity of their processes. 

Develop a Visual Appeal

Peoples' attention span is continuously reducing, making it more significant than ever to develop a visual appeal to measure their interest and be impactful. Data-driven storytelling adopts visuals, for instance, graphs and charts to communicate the insights to the end-user. 

The narratives and visuals permit clients to visualize the story behind their outcomes, which could help enhance client reporting. 

You spend less time explaining what's happening to others

You probably know your metrics and have your ways of obtaining that information. However, the minute you have to communicate what matters to others, things crumble. 

You find that they don't comprehend your dashboard or log into your CRM. Subsequently, you end up elucidating the information via email or in-person instead of spending that time on your work. With data storytelling, you don't have to worry about the explanation. Furthermore, you find that everybody is always on the same page. 


Dashboards can offer an effective solution to information overload, but only when designed properly. Most dashboards that businesses use today fail. They merely deliver a fraction of the needed insight to monitor a business at best. It's no wonder, they are gradually losing their significance and paving way for data storytelling. 

With Graphite Note we are putting efforts to combine traditional analytics, predictive analytics and data storytelling in easy to use SaaS environment.

RFM Analysis and Its Role in Customer Valuation

"Instead of focusing on the competition, focus on the customer." - Scott Cook

Every marketer knows the customer is king. New age marketers know it is imperative to sift the best from the rest.

Deviating attention from customers who matter or treating them the same as the others can endanger customer relationships. Building a loyal relationship with the best customers or converting prospects into repeat customers can be pivotal in turning any business around.

But how can you evaluate customers based on the value they bring to the company? Enter RFM analysis, a popular and verified method of customer valuation.

Speculated to be introduced in a 1995 article by Jan Roelf Bult and Tom Wansbeek, RFM analysis has remained a marketer’s favorite in understanding customers.

What is RFM Analysis?

RFM analysis is an acronym for Recency, Frequency, and Monetary Value Analysis that enables smart marketers to segregate their customer base. The technique borrows from the Pareto Principle, according to which 80% of a business’s revenue comes from 20% of its customers.

RFM analysis quantifies customers based on three key factors:

Image Source: unsplash.com

RFM analysis helps marketers figure out:

The RFM Score

Customers are scored individually on all three aspects. The total tally is an average of all three scores. The best customers score high in each of the three specified fields and have a high RFM score.

Usually, each of the three individual scores is given equal weightage when calculating the average. But this can vary depending upon the types of business you’re engaged in.

Consider a retail business. It is common for customers to make multiple purchases in a small span of time, say a month. The transaction value of retail purchases may not be very high. In such cases, an ideal RFM score can be calculated by giving more weightage to Recency and Frequency.

Why is RFM Analysis Important?

RFM analysis helps businesses understand their customers better and engage with them in a bespoke manner. It can help you to:

In short, RFM analysis could make a tangible difference to your business in terms of profitability and customer retention.

RFM Analysis in Graphite Note

Customer Segmentation Based on RFM Analysis

Customers can be segregated into the following categories depending upon their RFM analysis scores:

Best Customers

Such customers keep on buying your products or services on a regular basis. They also tend to have a good spending capacity and make big purchases. They are most likely to try out your newest launches and even promote your business among their peers.

Prospective Loyalists

Recent customers who make repeat purchases but are not very frequent fall under this category. These customers, if cultivated well with loyalty programs, discounts, etc. have the potential of becoming loyalists in future.

New Entrants

There are some customers who score high in RFM analysis but do not make regular purchases. Such ‘new entrants’ can be profitable for your business in the long run. Engage with them through various means to increase the frequency of their visits to your website.

Endangered Customers

Customers who used to make big and frequent purchases but have stopped doing so in recent times fall under this category.

Almost Lost Customers

These are customers who were once among your best but have shown a decline of interest over time. You must communicate with them to understand their change of heart and make every effort you can to win them back.


RFM analysis is a surefire way of allowing marketers to make discernible changes in their practices to help retain customers.

Graphite Note strives to provide such marketers with data stories built with the help of predictive analytics to create a time-efficient, pro-tech solution to their data analysis needs.

There is a way to improve Data Literacy in Companies today

Over the last decade, data has become an important part of any organization. But over the last few years, it has become essential for the growth, productivity, and success of companies across the globe. We are gathering an immense amount of data, which provides insights into everything from consumer behavior to company finances when used in the right way. Business intelligence (BI) techniques and Predictive Analytics are undoubtedly helping organizations manage data; however, this still requires data literacy. 

The problem is that companies are lacking AI and data literacy skills. Gartner predicts that by the end of 2050, 50% of organizations will not have sufficient data literacy skills. This means that companies won't be able to achieve the necessary value. In order to gain the most from data and new technologies, companies must begin to improve data literacy.

What Is Data Literacy?

Data literacy is considered a Key Performance Indicator (KPI) for companies in today's market. Whereas not so long ago, it was limited to the ability to read and write, the skill set required by employees has now expanded.

For an employee to successfully and accurately solve problems, they must be able to read, write, and communicate data in the relevant context.

They also need to understand the sources of data, how it is constructed, and the methods used to analyze it. On top of this, it's essential to know how to explain use cases, applications, and resulting values. 

It is more than likely that most companies have begun the process of creating a data-driven organization and are already taking advantage of better decision making. They have also managed to incorporate the ethical and legal side of data protection and transparency. As much as 90% of data and analytics decision-makers are aware of making data insights in decision making a priority. Nevertheless, this is still a huge struggle for most. 

Source: Unsplash

Why Is Data Literacy a Struggle?

While everyone is aware of the importance of data, not everyone is aware of its role in their job. It can no longer be done to the data analysts to be responsible for data literacy. As data becomes more important, everybody within an organization will need to know how data impacts their work. It is also possible that data professionals don't have a clear enough understanding of their work in the business context. 

As the volume of data continues to grow, it is becoming more and more difficult for those without the technical knowledge to keep up with those who are data-savvy. Censuswide reported data literacy findings after surveying over 7,000 business decision-makers worldwide:

How to Improve Data Literacy Within Your Organization

It's much wiser to begin creating and implementing data literacy strategies now as the amount of data your company acquires is only going to grow. While the main goal is to assist the data decision-makers, it is also necessary to improve the knowledge of those employees who aren't quite so tech-savvy. Here are six ways to start improving your data literacy:

Employees companywide need to be aware of the importance of data. Being data illiterate is not just a technical problem; it is one that will, at some point, spread across the entire company. Making everyone see that it is a company issue rather than just down to the tech department will enhance employee engagement. This drive in data literacy importance needs to come from the top, so it is the executives, managers, and leaders' responsibility. To develop data-driven mindsets, employees will need to understand why data is necessary and how it is used across all business processes. 

If you wake up one morning and say, "From today, we are all going to be data literate," you run the risk of putting non-technical employees off the transition. This is a process that requires starting small. You might feel that there is a rush, but when significant changes go about too fast, mistakes are made, and this reduces employee enthusiasm. It is better to start small, allow other employees to see the success so that they are more inclined to want to be a part of it. Aside from this, there is no room for error regarding confidential data, so only those with experience should be handlining it.

For those who aren't familiar with data or the associated technologies, it can be an overwhelming experience, especially for massive amounts of data. It is important to contextualize the data for them based on their role, experience, and background so that they are better able to effectively use the data.

Data literacy is a skill that will continue to grow. Once employees and teams master their data sets, provide access to more data so that they are able to explore and learn independently. People will need the opportunity to learn from their own mistakes by trying different strategies so that they are better prepared. That being said, certain data cannot be used for learning purposes, for example, confidential information.

Access alone is not enough. Employees to be taught how to use the data to the best advantage. After all, anyone can have access to data; this doesn't make them literate. As the statistics suggest, most employees are keen to learn essential data skills, so it is unlikely that there will be resistance. Ensure employees know how to interpret data as well as providing critical thinking training. 

Not every system or tool will be suitable for your company's needs. The system you choose needs to allow data analysts to share data across the company to relevant departments. Simultaneously, the systems you put in place need to be user-friendly for non-technical employees. If they cannot use it, the investment won't be used to its full potential. 

Graphite Data Story Notebook

Why is Graphite the Ideal Data Literacy Tool

With Graphite, it becomes easier to uncover hidden patterns, identify problems sooner, and see opportunities in your raw data. To run predictive analytics, without writing a single line of code.

And icing on the cake is - all team members can see the story of your data. 

An analyst can prepare a beautiful data story in Graphite Notebook, and share that insights and conclusions with all decision-makers and senior leaders that aren't confident to work with data and need help to understand it.

That is the Graphite Vision.