6 items tagged "storytelling"

  • 13 Tips & Techniques to use when Visualizing Data

    13 Tips & Techniques to use when Visualizing Data

    “By visualizing information, we turn it into a landscape that you can explore with your eyes. A sort of information map. And when you’re lost in information, an information map is kind of useful.” – David McCandless

    Did you know? 90% of the information transmitted to the brain is visual.

    Concerning professional growth, development, and evolution, using data-driven insights to formulate actionable strategies and implement valuable initiatives is essential. Digital data not only provides astute insights into critical elements of your business but if presented in an inspiring, digestible, and logical format, it can tell a tale that everyone within the organization can get behind.

    Data visualization methods refer to the creation of graphical representations of information. Visualization plays an important part in data analytics and helps interpret big data in a real-time structure by utilizing complex sets of numerical or factual figures.

    With the seemingly infinite streams of data readily available to today's businesses across industries, the challenge lies in data interpretation, which is the most valuable insight into the individual organization as well as its aims, goals, and long-term objectives.

    That's where data visualization comes in.

    Due to the way the human brain processes information, presenting insights in charts or graphs to visualize significant amounts of complex data is more accessible than relying on spreadsheets or reports.

    Visualizations offer a swift, intuitive, and simpler way of conveying critical concepts universally – and it's possible to experiment with different scenarios by making tiny adjustments.

    Recent studies discovered that the use of visualizations in data analytics could shorten business meetings by 24%. Moreover, a business intelligence strategy with visualization capabilities boasts a ROI of $13.01 back on every dollar spent.

    Therefore, the visualization of data is critical to the sustained success of your business and to help you yield the most possible value from this tried and tested means of analyzing and presenting vital information. To keep putting its value into perspective, let’s start by listing a few of the benefits businesses can reap from efficient visuals. 

    Benefits Of Data Visualization Skills & Techniques

    As we just mentioned in the introduction, using visuals to boost your analytical strategy can significantly improve your company’s return on investment as well as set it apart from competitors by involving every single employee and team member in the analysis process. This is possible thanks to the user-friendly approach of modern online data analysis tools that allow an average user, without the need for any technical knowledge, to use data in the shape of interactive graphs and charts in their decisions making process. Let’s look at some of the benefits data visualization skills can provide to an organization. 

    • Boosts engagement: Generating reports has been a tedious and time-consuming task since businesses and analytics came together. Not only are static reports full of numbers and text quickly outdated, but they are also harder to understand for non-technical users. How can you get your employees to be motivated and work towards company goals when they might not even understand them? Data visualizations put together in intuitive dashboards can make the analysis process more dynamic and understandable while keeping the audience engaged.  
    • Makes data accessible: Following up on the accessibility point, imagine you are an employee that has never worked with data before, trying to extract relevant conclusions from a bunch of numbers on a spreadsheet can become an unbearable task. Data visualizations relieve them from that burden by providing easy access to relevant performance insights. By looking at well-made graphs and charts, employees can find improvement opportunities in real-time and apply them to their strategies. For instance, your marketing team can monitor the development of their campaigns and easily understand at a glance if something is not going as expected or if they exceeded their initial expectations. 
    • They save time: No matter the business size, it is very likely that you are working with raw data coming from various sources. Working with this raw data as it is can present many challenges, one of them being the amount of time that it takes to analyze and extract conclusions from it. A time that could be spent on other important organizational or operational tasks. With the right data visualization tools and techniques, this is not an issue, as you can quickly visualize important performance indicators in stunning charts within seconds.  Like this, you can build a complete story, find relationships, make comparisons, and navigate through the data to find hidden insights that might otherwise remain untapped. 

    13 Tips & Techniques to use when Visualizing Data

    Now that you have a better understanding of how visuals can boost your relationship with data, it is time to go through our top techniques, methods, and skills needed to extract the maximum value out of this analytical practice. Here are 13 essential data visualization techniques you should know.

    1. Know Your Audience

    This is one of the most overlooked yet vital concepts around.

    In the grand scheme of things, the World Wide Web and Information Technology as a concept are in their infancy - and data visualization is an even younger branch of digital evolution.

    That said, some of the most accomplished entrepreneurs and executives find it difficult to digest more than a pie chart, bar chart, or a neatly presented visual, nor do they have the time to delve deep into data. Therefore, ensuring that your content is both inspiring and tailored to your audience is one of the most essential data visualization techniques imaginable.

    Some stakeholders within your organization or clients and partners will be happy with a simple pie chart, but others will be looking to you to delve deeper into the insights you’ve gathered. For maximum impact and success, you should always conduct research about those you’re presenting to prior to a meeting, and collate your report to ensure your visuals and level of detail meet their needs exactly.

    2. Set Your Goals

    Like any business-based pursuit, from brand storytelling right through to digital selling and beyond - with the visualization of your data, your efforts are only as effective as the strategy behind them.

    To structure your visualization efforts, create a logical narrative and drill down into the insights that matter the most. It’s important to set a clear-cut set of aims, objectives, and goals prior to building your management reports, graphs, charts, and additional visuals.

    By establishing your aims for a specific campaign or pursuit, you should sit down in a collaborative environment with others invested in the project and establish your ultimate aims in addition to the kind of data that will help you achieve them.

    One of the most effective ways to guide your efforts is by using a predetermined set of relevant KPIs for your project, campaigns, or ongoing commercial efforts and using these insights to craft your visualizations.

    3. Choose The Right Chart Type

    One of the most effective data visualization methods on our list; is to succeed in presenting your data effectively, you must select the right charts for your specific project, audience, and purpose.

    For instance, if you are demonstrating a change over a set of time periods with more than a small handful of insights, a line graph is an effective means of visualization. Moreover, lines make it simple to plot multiple series together.

    4. Take Advantage Of Color Theory

    The most straightforward of our selected data visualization techniques - selecting the right color scheme for your presentational assets will help enhance your efforts significantly.

    The principles of color theory will have a notable impact on the overall success of your visualization model. That said, you should always try to keep your color scheme consistent throughout your data visualizations, using clear contrasts to distinguish between elements (e.g. positive trends in green and negative trends in red).

    As a guide, people, on the whole, use red, green, blue, and yellow as they can be recognized and deciphered with ease.

    5. Handle Your Big Data

    With an overwhelming level of data and insights available in today’s digital world - with roughly 1.7 megabytes of data to be generated per second for every human being on the planet by the year 2020 - handling, interpreting, and presenting this rich wealth of insight does prove to be a real challenge.

    To help you handle your big data and break it down for the most focused, logical, and digestible visualizations possible, here are some essential tips:

    • Discover which data is available to you and your organization, decide which is the most valuable, and label each branch of information clearly to make it easy to separate, analyze, and decipher.
    • Ensure that all of your colleagues, staff, and team members understand where your data comes from and how to access it to ensure the smooth handling of insights across departments.
    • Keep your data protected and your data handling systems simple, digestible, and updated to make the visualization process as straightforward and intuitive as humanly possible.
    • Ensure that you use business dashboards that present your most valuable insights in one easy-to-access, interactive space - accelerating the visualization process while also squeezing the maximum value from your information.

    6. Use Ordering, Layout, And Hierarchy To Prioritize

    Following on our previous point, once you’ve categorized your data and broken it down to the branches of information that you deem to be most valuable to your organization, you should dig deeper, creating a clearly labeled hierarchy of your data, prioritizing it by using a system that suits you (color-coded, numeric, etc.) while assigning each data set a visualization model or chart type that will showcase it to the best of its ability.

    Of course, your hierarchy, ordering, and layout will be in a state of constant evolution but by putting a system in place, you will make your visualization efforts speedier, simpler, and more successful.

    7. Utilize Word Clouds And Network Diagrams

    To handle semi-structured or decidedly unstructured sets of data efficiently, you should consult the services of network diagrams or cloud words.

    A network diagram is often utilized to draw a graphical chart of a network. This style of layout is useful for network engineers, designers, and data analysts while compiling comprehensive network documentation.

    Akin to network diagrams, word clouds offer a digestible means of presenting complex sets of unstructured information. But, as opposed to graphical assets, a word cloud is an image developed with words used for particular text or subject, in which the size of each word indicates its frequency or importance within the context of the information.

    8. Use Text Carefully 

    So far, we’ve made it abundantly clear that the human brain processes visuals better than text. However, that doesn’t mean you should exclude text altogether. When building efficient graphics with your data, the use of text plays a fundamental role in making the graphs understandable for the audience. That said, it should be used carefully and with a clear purpose. 

    The most common text elements you can find in data visualizations are often captions, labels, legends, or tooltips just to name a few. Let’s look at each of them in a bit more detail. 

    • Captions: The caption occupies the top place in a graph or chart and it tells the user what he or she should look for in that visual. When it comes to captions you should always avoid verbosity. Keep them short and concise and always add the units of measurement. 
    • Labels: Labels describe a value associated with a specific data point in the chart. Here it is important to keep them short, as too long labels can crowd the visual and make it hard to understand. 
    • Legends: A legend is a side section of a chart and it shows and it gives a brief description to help users understand the data being displayed. For example, what each color means. A good practice when it comes to legends is to arrange them per order of appearance. 
    • Tooltip: A tooltip is a visualization technique that allows you to add extra information to your graphs to make them more clear. Now, adding them under each data point would totally overcrowed them. Instead, you should rely on interactive tooltips that show the extra text once the user hovers over the data point. 

    By following these best practices you will make sure your text brings an added value to your visuals instead of making them crowded and harder to read. 

    9. Include Comparisons

    This may be the briefest of our data visualization methods, but it’s important nonetheless: when you’re presenting your information and insights, you should include as many tangible comparisons as possible. By presenting two graphs, charts, and diagrams together, each showing contrasting versions of the same information over a particular timeframe, such as monthly sales records for 2016 and 2017 presented next to one another, you will provide a clear-cut guide on the impact of your data, highlighting strengths, weaknesses, trends, peaks, and troughs that everyone can ponder and act upon.

    10. Tell Your Tale

    Similar to content marketing, when you're presenting your data in a visual format with the aim of communicating an important message or goal, telling your story will engage your audience and make it easy for people to understand with minimal effort.

    Scientific studiesconfirm that humans, in large, respond better to a well-told story, and by taking this approach to your visualization pursuits, you will not only dazzle your colleagues, partners, and clients with your reports and presentations, but you will increase your chances of conveying your most critical messages, getting the buy-in and response you need to make the kind of changes that will result in long-term growth, evolution and success.

    To do so, you should collate your information, thinking in terms of a writer, establishing a clear-cut beginning, middle, and end, as well as a conflict and resolution, building tension during your narrative to add maximum impact to your various visualizations.

    11. Merge It All Together

    Expanding on the point above, in order to achieve an efficient data storytelling process with the help of visuals, it is also necessary to merge it all together into one single location. In the past, this was done with the help of endless PowerPoint presentations or Excel sheets. However, this is no longer the case thanks to modern dashboard technology. 

    Dashboards are analytical tools that allow users to visualize their most important performance indicators all on one screen. This way, you avoid losing time by looking at static graphs that make the process tedious. Instead, you get the possibility to interact and navigate them to extract relevant conclusions in real-time. Now, dashboard design has its own set of best practices that you can explore, however, they are still similar to the ones mentioned throughout this post.

    12. Consider The End Device

    As we almost reach the end of our list of insightful data visualization methods, we couldn’t leave a fundamental point behind. We live in a fast-paced world where decisions need to be made on the go. In fact, according to Statista, 56,89% of the global online traffic corresponds to mobile internet traffic. With that in mind, it is fundamental to consider device versatility when it comes to building your visuals and ensuring an excellent user experience.   

    We already mentioned the importance of merging all your visuals together into one intuitive business dashboard to tell a complete story. When it comes to generating visuals for mobile, the same principles apply. Considering that these screens are smaller than desktops, you should make sure to only include the graphs and charts that will help you convey the message you want to portray. You should also consider the size of labels and buttons as they can be harder to see on a smaller device. Once you have managed all these points, you need to test on different devices to ensure that everything runs smoothly.  

    13. Apply Visualization Tools For The Digital Age

    We live in a fast-paced, hyper-connected digital age that is far removed from the pen and paper or even copy and paste mentality of the yesteryears - and as such, to make a roaring visualization success, you should use the digital tools that will help you make the best possible decisions while gathering your data in the most efficient, effective way.

    A task-specific, interactive online dashboard or tool offers a digestible, intuitive, comprehensive, and interactive means of collecting, collating, arranging, and presenting data with ease - ensuring that your techniques have the most possible impact while taking up a minimal amount of your time.

    Summary

    As seen throughout this guide, data visualizations allow users and businesses to make large volumes of relevant data more accessible and understandable. With markets becoming more competitive by the day, the need to leverage the power of data analytics becomes an obligation instead of a choice, and companies that understand that will have a huge competitive advantage. 

    Author: Bernardita Calzon

    Source: Datapine

  • 5 Tips to increase the connectedness of your employees

    5 Tips to increase the connectedness of your employees

    Helping your employees build workplace connections is critical if you want to attract and retain talent. People who feel like they belong and have workplace friendships are happier, healthier and more engaged.

    "One of the best things about working for StoneAge is my relationships with co-workers. I love the people I work with! I learned something new about one of my teammates the other day, and everything clicked. Now I understand why she gets defensive when I ask her questions about her ideas. I was only curious about her thought process, but she told me about a past experience that, when triggered, causes her to get defensive when asked questions. Learning this was helpful; now, I know how to reframe my questions, so we have a productive conversation. I feel way more connected to her now."

    This recent conversation with one of my employees warmed my heart. In fact, I couldn't have been happier. If there is one thing I want to create at StoneAge, it's deeper personal and professional connections at all levels of the organization.

    Why do I care so much about workplace connection? Because I want the work experience at my company to enrich people's lives, and having healthy relationships does just that. I also want my employees to want to work here — attracting, retaining and developing talent is what will make or break companies now and in the future. The Great Resignation is showing us this. Across the country, people are leaving their jobs in droves, because they feel disconnected from their bosses, teammates and companies. Many workers are lonely, and when underpaid and overworked, they say, "Enough is enough." At my company, we know the secret is connection. The connection between employees and management. The connection between each other as peers and human beings.

    Our employees aren't the only ones saying workplace connections matter. The Institute of Leadership and Management published a report stating that 77% of survey respondents said that close relationships with colleagues were the most critical factors when determining job satisfaction. But not many employees have these deep connections. According to the Gallup Organization, a global analytics and advice firm, only 30% of employees have a best friend at work. Employees with a best friend at work are more likely to engage customers, produce better work, have higher well-being and are less likely to get injured. In fact, according to Gallup, employees who have a best friend at work are seven times more engaged.

    So, how do you go about building strong workplace connections? Here are five things you can start doing now:

    1. Make connecting a priority

    Start every meeting off with a check-in. We state how we are feeling and why, and it's wonderful how this helps foster connection and empathy. Additionally, at the beginning of our monthly company meetings, employees meet in virtual breakout rooms to share personal stories, give an update,and express gratitude to people on their team. These small opportunities go a long way toward creating better workplace relationships and deeper connections. In fact, when we surveyed our employees about what helped them feel more connected at work, they resoundingly said the breakout sessions at monthly company meetings were powerful ways to get to know each other.

    2. Encourage storytelling

    In my experience, sharing stories with vulnerability and openness sparks curiosity, helps people understand each other and makes people feel like they belong. During my weekly team meetings, we take turns telling a personal story. It's incredible what we learn about each other, and the newfound insight helps us work through conflict and issues. For example, one of my direct reports shared a story about how hard his dad was on him growing up. The damage from the relationship caused him to question his value to our team, and he never felt like he measured up. This vulnerability helped us understand why he was so hard on himself, and we found ways to help him move through his self-doubt faster. None of that would have been possible if he hadn't shared this deeply personal story.

    3. Give all new employees a culture buddy

    According to research by O.C. Tanner Institute, 69% of employees are more likely to stay with a company for three years if they experience great onboarding. A good onboarding process involves helping new employees feel connected to their peers and supervisors. Still, it's hard for new employees to feel connected, especially in a remote or hybrid work environment. To help with this, assign new employees a culture buddy with whom they can connect every day to ask questions about where to go for information and how to navigate the culture. We've found this very engaging for both the new hire and the more established culture buddy.

    4. Create more dialogue

    Most people crave more interaction with leadership, so create opportunities to have more dialogue with your employees. The best way to foster a connection is to have a conversation. Pick up the phone to see how someone is doing. Go for a walk with a colleague. I call at least five employees every week to see how they are doing and foster a connection, and I am always surprised by what I learn. My employees tell me how much they appreciate these check-ins and how they help them feel like they belong on the team. It's not easy to scale, but I believe that building connections isn't about scale; it's about depth.

    5. Rally around teamwork

    To foster connection across the broader organization, you must codify what it means to be part of the team. At my company, we rally around a "One Team" mentality, which helps people understand that we are all in this together and must work as one united, company-wide team rather than a set of individual teams. We celebrate "One Team" efforts and showcase how almost everything we do requires all of us, not just an individual or a single team. "One Team" encourages collaboration and teamwork, fosters inclusivity and connection, keeps people focused on the collective good and helps everyone consider that their decisions impact everyone throughout the organization.

    Helping your employees build workplace connections is critical if you want to attract and retain talent. People who feel like they belong and have workplace friendships are happier, healthier and more engaged. It takes time and intention, but it's worth the effort — connection is how you build a great place to work.

    Author: Kerry Siggins

    Source: Entrepreneur

  • Data alone is not enough, storytelling matters - part 1

    Data alone is not enough, storytelling matters - part 1

    Crafting meaningful narratives from data is a critical skill for all types of decision making, in business, and in our public discourse

    As companies connect decision-makers with advanced analytics at all levels of their organizations, they need both professional and citizen data scientists who can extract value from that data and share. These experts help develop process-driven data workflows, ensuring employees can make predictive decisions and get the greatest possible value from their analytics technologies.

    But understanding data and communicating its value to others are two different skill sets. Your team members’ ability to do the latter impacts the true value you get from your analytics investment. This can work for or against your long-term decision-making and will shape future business success.

    There are between stories and their ability to guide people’s decisions, even in professional settings. Sharing data in a way that adds value to decision-making processes still requires a human touch. This is true even when that data comes in the form of insights from advanced analytics.

    That’s why data storytelling is such a necessary activity. Storytellers convert complex datasets into full and meaningful narratives, rich with visualizations that help guide all types of business decisions. This can happen at all levels of the organization with the right tools, skill sets, and workflows in place. This article highlights the importance of data storytelling in enterprise organizations and illustrates the value of the narrative in decision-making processes.

    What is data storytelling?

    Data storytelling is an acquired skill. Employees who have mastered it can make sense out of a body of data and analytics insights, then convey their wisdom via narratives that make sense to other team members. This wisdom helps guide decision making in an honest, accurate, and valuable way.

    Reporting that provides deep, data-driven context beyond the static data views and visualizations is a structured part of a successful analytic lifecycle. There are three structural elements of data storytelling that contribute to its success:

    • Data: Data represents the raw material of any narrative. Storytellers must connect the dots using insights from data to create a meaningful, compelling story for decision-makers.
    • Visualization: Visualization is a way to accurately share data in the context of a narrative. Charts, graphs, and other tools “can enlighten the audience to insights that they wouldn’t see without [them],” Forbes observes, where insights might otherwise remain hidden to the untrained eye.

    • NarrativeA narrative enables the audience to understand the business and emotional importance of the storyteller’s findings. A compelling narrative helps boost decision-making and instills confidence in decision-makers.

    In the best cases, storytellers can craft and automate engaging, dynamic narrative reports using the very same platform they use to prepare data models and conduct advanced analytics inquiries. Processes may be automated so that storytellers can prepare data models and conduct inquiries easily as they shape their narrative. But whether the storyteller has access to a legacy or modern business intelligence (BI)platform , it’s the storyteller and his or her capabilities that matter most.

    Who are your storytellers?


    "The ability to take data - to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it - that’s going to be a hugely important skill in the next decades."

    Hal R. Varian, Chief Economist, Google, 2009


    The history of analytics has been shaped by technical experts, where companies prioritized data scientists who can identify and understand raw information and process insights themselves. But as business became more data-driven, the need for insights spread across the organization. Business success called for more nuanced approaches to analysis and required broader access to analytics capabilities.

    Now, organizations more often lack the storytelling skill set - the ability to bridge the gap between analytics and business value. Successful storytellers embody this 'bridge' as a result of their ability to close the gap between analytics and business decision-makers at all levels of the organization.

    Today, a person doesn’t need to be a professional data scientist to master data storytelling. 'Citizen data scientists' can master data storytelling in the context of their or their team’s decision-making roles. In fact, the best storytellers have functional roles that equip them with the right vocabulary to communicate with their peers. It’s this “last mile” skill that makes the difference between information and results.

    Fortunately, leading BI platforms provide more self-service capabilities than ever, enabling even nontechnical users to access in-depth insights appropriate to their roles and skill levels. More than ever, employees across business functions can explore analytics data and hone their abilities in communicating its value to others. The question is whether or not you can trust your organization to facilitate their development.

    This is the end of part 1 of this article. To continue reading, you can find part 2 here.

    Author: Omri Kohl 

    Source: Pyramid Analytics

  • Data alone is not enough, storytelling matters - part 2

    Data alone is not enough, storytelling matters - part 2

    This article comprises the second half of a 2 part piece. Be sure to read part 1 before reading this article.

    Three common mistakes in data storytelling

    Of course, there are both opportunities and risks when using narratives and emotions to guide decision-making. Using a narrative to communicate important data and its context means listeners are one-step removed from the insights analytics provide.

    These risks became realities in the public discourse surrounding the 2020 global COVID-19 pandemic. Even as scientists recommended isolation and social distancing to ´flatten the curve´ - low the spread of infection - fears of an economic recession grew rampant. Public figures often overlooked inconvenient medical data in favor of narratives that might reactivate economic activity, putting lives at risk.

    Fortunately, some simple insights into human behavior can help prevent large-scale mistakes. Here are three common ways storytellers make mistakes when they employ a narrative, along with a simple use case to illustrate each example:

    • 'Objective' thinking: In this case, the storyteller focuses on an organizational objective instead of the real story behind the data. This might also be called cognitive bias. It’s characterized by the storyteller approaching data with an existing assumption rather than a question. The analyst therefore runs the risk of picking data that appears to validate that assumption and overlooking data that does not.

      Imagine a retailer who wants to beat its competitor’s customer service record. Business leaders task their customer experience professionals with proving this is the case. Resolute on meeting expectations, those analysts might omit certain data that doesn’t tip the results in favor of the desired outcome.

    • 'Presentative' thinking: In this case, the storyteller focuses on the means by which he or she presents the findings - such as a data visualization method - at risk of misleading, omitting, or watering down the data. The storyteller may favor a visualization that is appealing to his or her audience at the expense of communicating real value and insights.

      Consider an example from manufacturing. Imagine a storyteller preparing a narrative about productivity for an audience that prefers quantitative data visualization. That storyteller might show, accurately, that production and sales have increased but omit qualitative data analysis featuring important customer feedback.

    • 'Narrative' thinking: In this case, the storyteller creates a narrative for the narrative’s sake, even when it does not align well with the data. This often occurs when internal attitudes have codified a specific narrative about, say, customer satisfaction or performance.

      During the early days of testing for COVID-19, the ratio of critical cases to mild ones appeared high because not everyone infected had been tested. Despite the lack of data, this quickly solidified a specific media narrative about the lethality of the disease.

    Business leaders must therefore focus on maximizing their 'insight-to-value conversion rate', as Forbes describes it, where data storytelling is both compelling enough to generate action and valuable enough for that action to yield positive business results. Much of this depends on business leaders providing storytellers with the right tools, but it also requires encouragement that sharing genuine and actionable insights is their top priority.

    Ensuring storytelling success


    “Numbers have an important story to tell. They rely on you to give them a clear and convincing voice.”

    Stephen Few, Founder & Principal, Perceptual Edge®


    So how can your practical data scientists succeed in their mission: driving positive decision-making with narratives that accurately reflect the story behind the data your analytics provide? Here are some key tips to relay to your experts:

    • Involve stakeholders in the narrative’s creation. Storytellers must not operate in a vacuum. Ensure stakeholders understand and value the narrative before its official delivery.

    • Ensure the narrative ties directly to analytics data. Remember, listeners are a step removed from the insights your storytellers access. Ensure all their observations and visualizations have their foundations in the data.

    • Provide deep context with dynamic visualizations and content. Visualizations are building blocks for your narrative. With a firm foundation in your data, each visualization should contribute honestly and purposefully to the narrative itself.

    • Deliver contextualized insights. 'Know your audience' is a key tenant in professional writing, and it’s equally valuable here. Ensure your storytellers understand how listeners will interpret certain insights and findings and be ready to clarify for those who might not understand.

    • Guide team members to better decisions. Ensure your storytellers understand their core objective - to contribute honestly and purposefully to better decision-making among their audience members.

    As citizen data science becomes more common, storytellers and their audience of decision-makers are often already on the same team. That’s why self-service capabilities, contextual dashboards, and access to optimized insights have never been so critical to empowering all levels of the organization.

    Getting started: creating a culture of successful storytelling

    Insights are only valuable when shared - and they’re only as good as your team’s ability to drive decisions with them in a positive way. It’s data storytellers who bridge the gap from pure analytics insights to the cognitive and emotional capacities that regularly guide decision-making among stakeholders. As you might have gleaned from our two COVID-19 scenarios, outcomes are better when real data, accurate storytelling, and our collective capacities are aligned.

    But storytellers still need access to the right tools and contextual elements to bridge that gap successfully. Increasing business users’ access to powerful analytics tools is your first step towards data storytelling success. That means providing your teams with an analytics platform that adds meaning and value to business decisions, no matter their level in your organization.

    If you haven´t read part 1 of this article yet, you can find it here.

    Author: Omri Kohl

    Source: Pyramid Analytics

  • Data storytelling: 5 best practices

    Data storytelling: 5 best practices

    Learn how to hone both your verbal and written communication skills to make your insights memorable and encourage decision-makers to revisit your research.

    You’ve spent months collecting data with your insights team or research vendors, and you’ve compiled your research into a presentation that you think is going to blow your audience away. But what happens after you’ve finished presenting? Do your stakeholders act on the insights you’ve shared, or do they move on to their next meeting and quickly forget your key takeaways and recommendations?

    If you want to avoid the latter, it’s important to consider how you can make the biggest possible impact while presenting and also encourage your stakeholders to revisit your research after the fact. And that requires you to hone both your verbal and written communication skills.

    In other words: practice your storytelling.

    Research shows that combining statistics with storytelling results in a retention rate of 65-70%. So, how do you take advantage of this fact when presenting and documenting your insights?

    Below are five best practices to help you present insights through stories – and encourage your stakeholders to revisit those stories as they make business decisions.

    Tailor the message to your audience

    To maximize the impact of your story, you have to consider who’s hearing it.

    When you’re presenting to someone in finance, try to cover how your findings can help the company save money. When you’re talking to Marketing or Sales, explain how the information can drive new leads and close more deals. When you’re talking to the product development team, explain how they can deliver a better solution.

    The more you can address your audience’s concerns in the language they use and the context they understand, the bigger the impact your story will have.

    Ask yourself:

    1. How much does my audience already know about the subject I’m covering?
    2. How much time do they have to listen to what I’m saying?
    3. What are their primary concerns?
    4. What type of language do they use to communicate?
    5. Are there preconceptions I need to address?

    If your insights are applicable to multiple groups across the organization, it’s worth thinking about how you can tweak the story for each audience. This could mean writing different sets of key takeaways and implications for different groups or altering the examples you use to better align with each audience’s interests.

    Follow the structure of a story

    While stories come in various shapes, sizes, tones, and genres, they all have a few things in common – one of those being a similar structure.

    Think about how a movie is typically divided into three acts. Those acts follow this general structure:

    1. Setup: We’re introduced to the protagonist, and they experience some kind of inciting incident (i.e., the introduction of conflict or tension) that propels the story forward.
    2. Confrontation: The protagonist works to achieve a goal but encounters obstacles along the way.
    3. Resolution: The protagonist reaches the height of their conflict with an antagonist and achieves some kind of outcome (whether it’s the protagonist’s desired outcome or not will depend on the type of story).

    Here’s a (fictional) example of an insights-driven story that follows this structure:

    1. The insights team for a beverage company shares a recorded interview with a real customer, who we’ll call Raquel. Raquel talks about how she loves getting together for backyard barbecues with friends. She says that she used to always drink beer at these barbecues but has recently decided to stop drinking.
    2. Raquel goes on to say that she doesn’t really like soda because she thinks it’s too sweet, but she will often pick one up at barbecues because she wants to have a drink in her hand.
    3. After playing this interview, the insights team presents findings from their latest study into young women’s non-alcoholic beverage preferences. They use Raquel’s story to emphasize trends they are seeing for canned beverages with lower sugar or sweetener contents.

    By framing your data and reports in this narrative structure, you’re more likely to keep your audience interested, make your findings memorable, and emphasize how your findings relate to real customers or consumers. This is a great way to get business decision-makers to invest in and act on your insights.

    Put your editor’s hat on

    When you have managed or been directly involved with a research project, it can be tempting to include every fascinating detail in your presentation. However, if you throw extraneous information into your data story, you’ll quickly lose your audience. It’s important to put yourself in the mindset of your audience and ruthlessly edit your story down to its essential ingredients.

    According to Cinny Little, Principal Analyst at Forrester Research, you should focus on answering the audience’s two primary questions: “What’s in it for me?” and “Why do I need to care?”

    You should also keep your editor’s hat on when documenting your key recommendations or takeaways for a report. Studies show that people can only hold about four items in their conscious mind, or working memory, at any one time. If you include more than three or four recommendations, your audience will have a harder time retaining the most important information.

    Find your hook

    When presenting, don’t think you can start slow and build up excitement – research suggests you only have about 30 to 60 seconds to capture your audience’s attention. After that, you’ve lost them.

    And getting them back won’t be easy.

    That’s why you need a hook – a way to start your story that’s so engaging and compelling your audience can’t help but listen.

    According to Matthew Luhn, a writer, story consultant, and speaker who has experience working with Pixar, The Simpsons, and more, a compelling hook is at least one of the following:

    • Unusual
    • Unexpected
    • Action-filled
    • Driven by conflict

    When sharing your research, you could hook your audience by leading with a finding that goes against prevailing assumptions, or a specific example of a customer struggling with a problem that your product could solve. Find a hook that evokes a strong emotion so that your story will stick with listeners and drive them to make decisions.

    Experiment with your story medium

    If you present your research to a room (or Zoom meeting) full of stakeholders once and then move on, you’re limiting the reach, lifespan, and value of that research. At a time when so many teams have become decentralized and remote work is common, it’s more important than ever to preserve your data stories and make them accessible to your stakeholders on demand.

    At the most basic level, this could mean uploading your presentation decks to an insights management platform so that your stakeholders and team members can look them up whenever they want. However, it’s also worth thinking about other mediums you can translate your stories into. For example, you might publish infographics, video clips from customer interviews, or animated data visualizations alongside your reports. Think about the supporting materials you can include to bring the story to life for anyone who wasn’t in the room for the initial presentation.

    Conclusion

    ​​By applying the best practices above, you can take the data and reports that others often find dry (no matter how much you disagree) and turn them into compelling, engaging, and persuasive stories.

    This process of developing and distributing insights stories will enable you and your team to have a more strategic impact on your company as a whole by demonstrating the potential outcomes of making decisions based on research.

    Author: Madeline Jacobson

    Source: Greenbook

  • Toucan Toco introduceert realtime data-analyse voor franchiseformules

    Toucan Toco introduceert realtime data-analyse voor franchiseformules

    Interactieve tool geeft franchises datagestuurde inzichten om verkoop te stimuleren

    Toucan Toco, specialist in data storytelling, introduceert een bewezen effectieve analyse-oplossing voor franchise-ondernemingen nu ook in Nederland. De interactieve tool omvat een dashboard dat allerlei data voor franchiseformules visualiseert en daarmee belangrijke inzichten geeft om hun marktaandeel en klanttevredenheid te verbeteren en hun omzet te verhogen. Gebruikers profiteren bovendien van de kracht van data storytelling in de visualisatiemodule voor duidelijkere inzichten uit de bestaande data
     
    In tegenstelling tot conventionele franchisebeheersoftware biedt Toucan Toco een volledig interactieve oplossing voor het bijhouden van prestaties, waardoor franchisenemers snel toegang hebben tot conversiepercentages, verkoopgegevens, topproducenten en andere belangrijke prestatie-indicatoren. Resultaten en verschillen kunnen per franchise worden vergeleken en geanalyseerd. De analyses en data-inzichten kunnen vervolgens worden gebruikt om KPI-beheer aan te scherpen en continue optimalisatie te stimuleren, wat resultaten oplevert voor zowel individuele franchisenemers als de formule als geheel.
    Klanten die al met het dashboard werken, ervaren een stijging van het marktaandeel met 5 procent, een stijging van 7 procent in verkoopprestaties en een stijging van 3,5 procent in klanttevredenheid.
     
    Voor zowel franchiseformules als franchisenemers levert de analyse-oplossing voordelen op:

    Prestatie-optimalisatie

    Franchiseformules vertrouwen traditioneel op Excel-gebaseerde rapportagebestanden, waardoor het moeilijk is om slimme, datagestuurde beslissingen te nemen. Het datavisualisatieplatform van Toucan Toco vergelijkt KPI's en prestatiestatistieken tussen regio's, productlijnen, enzovoort, zodat franchises de prestaties continu kunnen inzien, begrijpen én verbeteren.  

    Betere communicatie

    Door gecentraliseerd databeheer beschikken managers door de hele organisatie, van hoofdkantoor tot lokale vestigingen, over dezelfde, begrijpelijke informatie en inzichten. Dit stelt managers in staat om sneller actie te ondernemen en slimmere te beslissingen nemen. 

    Nieuwe franchises aantrekken

    Met gedifferentieerde, gegevensgestuurde beheerprocessen is het voor nieuwe franchises gemakkelijker om te begrijpen wat er wordt verwacht, wat de huidige resultaten per vestiging zijn, de naleving te verifiëren en de aanwijzingen van het hoofdkantoor op te volgen. Dat resulteert in een eenvoudiger onboarding proces en betere communicatie over KPI’s en prestaties.

    Inzichten op elk device

    Franchise-medewerkers werken over het algemeen zonder vast bureau of PC, dus een mobile-first analyseplatform is essentieel. De oplossing van Toucan Toco is beschikbaar via mobiel, tablet en desktop, zodat medewerkers overal toegang hebben tot inzichten.
     
    Franchiseformules en franchisenemers profiteren bovendien van Toucan Toco’s expertise op het gebied van datacommunicatie voor beter begrip van data, ook door niet-dataspecialisten. Het geïntegreerde analyse-platform maakt gebruik van data storytelling voor eenvoudige en intuïtieve weergave van data in begrijpelijke, interactieve visualisaties, zodat organisatiebreed datagedreven beslissingen kunnen worden genomen.  
     
    “Een breed begrip van data door medewerkers en krachtige communicatie met data storytelling spelen een belangrijke rol in het verbeteren van de prestaties van franchiseformules en individuele franchisevestigingen”, zegt Baptiste Jourdan, mede-oprichter van Toucan Toco. “De analyse-oplossing voor franchiseformules is een mooie stap in onze missie om organisaties te helpen het maximale uit hun data te halen en alle medewerkers in staat te stellen om sneller de juiste beslissingen te nemen.”
     
    Bron: Toucan Toco

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