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Great businesses are founded on great data. But with so many insights available how do you handle it effectively?

At one end of the analytics spectrum, we have “static analytics” which consists of reports as fixed dashboards, presentations, pdfs, or images. This is the traditional way of displaying data where data is aggregated and then shared with internal stakeholders. The end users have to depend on the analyst who developed the report or dashboard in order to derive insights or answer specific questions from the data. However, this is long and super tiring process.

Then we have “self-service analytics” on the other end of the spectrum, which enables users to directly interact with data from its source and even create dashboards and derive insights on their own without having to depend on an analyst. Using a feature like “Explain Data” in Tableau Desktop or a natural language processing feature like “Ask Data” in Tableau Server are examples of self-service analytics.

Lastly, “Guided Analytics” in between static analytics and self-service analytics. Using the guided analytics approach, an analyst is still in charge of creating a dashboard, but the end users are empowered to quickly understand the information and functionality of the dashboard and leverage various options to slice and dice data through the interactivity layers made available in it. The dashboards are informative, user-friendly, and display better performance. Ultimately, the guided analytics is way of providing solutions or creating dashboards by keeping the end users in mind.

Why Guided Analytics?

To understand the importance of guided analytics, let us consider two key components, user experience and performance.

Creating a successful user experience is imperative for guided analytics, without it, adoption rates will be low. Dashboards should be created keeping end user in mind. They should be simple, flexible and intuitive, empowering the end user to interact with the dashboards easily.

Guided analytic dashboards when designed should consist of a clean, simple design and responsiveness. A dashboard becomes unattractive the longer time a user has to wait for the data to load and slow speeds when interacting with the data. To ensure you create a high-performance dashboard for guided analytics, make sure you limit the number of filters, target specific fields, use action filters instead of quick filters, and high responsiveness to user interactivity.

Core Principles of Guided Analytics

Designing Dashboards for Guided Analytics

Use this checklist to design user-friendly dashboards:

  1. Include an icon at the top left that tells about the purpose, summary, and parts or components of the dashboard.
  2. Use an appropriate title for dashboard that is dynamic (capable of reflecting the filtered or selected data) so that users are always able to see the context of what they are looking at..
  3. Minimize the number of colors used as too many can confuse end users. Best practice is to use 7 or less in a dashboard.
  4. Leverage tooltips to its fullest by including additional and relevant information by customizing tooltips and adding in sheets with additional information.
  5. Use system compatible fonts.
  6. Use action filters to drilldown to other charts that are not part of your dashboard itself.

Ready to get started? Get started in your analytic approach journey, and one of our analytics experts will consult with your company about where you want to go with your data.

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The role of data and analytics is rapidly changing from simply acting as a business-supporting function to being a catalyst for digital transformation.

Whether you like it or not, we are all generating and consuming data at an unprecedented pace. For example, Google now aggregates anonymized datasets from willing mobile users based on their device’s location history. It has built community mobility reports based on geolocation data and shared it for public use. In the current Covid-19 climate, this data has proved to be immensely useful for any organization that is looking to reopen and reimagine its operations.

As a leader of a corporation, government agency, university or nonprofit, it is likely that you use data every day to make choices that affect your business. If you were not already using data to drive decisions, the Covid-19 pandemic must have been a wake-up call for your organization. The ensuing economic disruption has forced businesses to adopt or accelerate their digital transformation journey as they adapt to changing market demands, reinventing offerings, optimizing resources and, in some cases, even fighting for survival. Data and analytics have become strategic and central to digital transformation, but Covid-19 has complicated this journey, making it more challenging to collaborate.

Based on our firm’s 16-year history of supporting customers across all industries and recent conversations with customers and our global centers of excellence, I’ve highlighted five success factors that CEOs should consider critical in their quest to derive maximum value from available data assets:

1. Put data and analytics at the heart of business strategy.

To create a sustainable competitive advantage for your business, you should invest in analytics as a core capability within your organization. This means a top-down commitment from executive leadership, investment in people, trustworthy data and insights made accessible to business users. This also means that you focus on ensuring that executives act on what the data tells them.

Do not assume that you must build analytics systems yourself to create a competitive advantage. If IT is not core to your business, find the right partner to help you build the analytics systems, and you focus on consumption and decision-making.

2. Plan for perpetual modernization.

Given the state of evolution of technology and data, IT leadership should reimagine how it designs data and analytics systems. The architecture itself should be evolutionary — including data systems, insight development and delivery systems. Without taking advantage of cloud, modern architectures and automation, you will not be able to fulfill the expectations of different users and their analytic intentions in the organization. Keep in mind that moving to the cloud should not take years of planning and execution. If needed, you can always keep your current systems working on-premise while you build the new systems in the cloud.

One of our customers moved a 2PB complex analytics system from an on-premise data center to the AWS cloud within nine months. You should adopt modular and technology-agnostic architectures with room to evolve and avoid lock-in to specific tools.

3. Revisit the business/IT engagement model.

To ensure that the value of analytics reaches the strategy and operational units, organizations should focus on how the business and IT work together. Various models are available — centralized, decentralized, supportive, consultative — so you can pick the one that works best for your organization. Not being consistent with how your business is organized is likely to create longer-term challenges. The good thing is, you can start with one model and evolve into the next based on your organizational maturity.

When one of our customers implemented self-service analytics capability across their business units, they established clear roles; IT was made responsible for the enterprise platform, and business units were made responsible for building and maintaining the applications.

4. Make insights accessible to users.

Data-informed decision-making is no longer an executive privilege. Data should be accessible to all staff so they can use or create their own insights for their jobs. IT teams do not need to create every single report and insight. They should also move away from trying to standardize the consumption tools. They should consider making insights available in the tools that the users are already comfortable with.

Insights should be understandable and actionable. Consider the use of techniques such as data storytelling to enable users to comprehend information easily and move toward actions. One of our customers uses automated commentary on top of visuals to convey specific actions to front-line staff.

5. Reimagine return on investment.

We all know that the Covid-19 pandemic has caused a significant shift in consumer demand and that most organizations have had to reevaluate what is important today and what will be relevant tomorrow. Traditional portfolio rationalization models use metrics that show a connection to the revenue or profit for justification and prioritization. However, return on investment encompasses more than just the financial impact; one must consider other factors, such as the potential of results from empowered employees, better customer experiences and newer capabilities.

Leaders must also find ways to explain the intangibles that come with informed decisions. Not everything can be black and white. For example, how do you quantify the impact of saving lives due to better insights? If Google’s community mobility report helps you keep your employees safe, get health care to those in need or bring a sense of normalcy into our lives, what is the investment that we are willing to make to use it?

Navigating organizations safely and effectively in the coming months will be a big challenge for all leaders. However, in times of uncertainty, making informed actions based on data is better than making decisions simply based on instincts. You do not have to drive into an unknown city without maps; you can invest in a navigation aid that you can afford and that makes sense for your business — it could be a paper-based map, a GPS or maybe even a Tesla. You have to make a choice.

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As seen on Forbes

Building a new tech product—or updating something you didn’t build initially—for a new client always comes with challenges. Addressing the client’s actual needs can be difficult, especially when you’re working with someone outside of your industry. They may not know how to fully communicate or describe what they want, which can make their asks vague and unclear.

To help you ensure you’re giving the best service to your non-tech clients, we asked members of Forbes Technology Council what questions they ask to clarify a new client’s project. They recommend asking these questions to get both of you on the same page.

1. ‘What are you trying to do?’

Understanding the business value and using that as a driver for technology evaluation and selection is crucial. The business value, or return on investment, must drive technology decisions, not the other way around. A mentor of mine once told me, “In IT, there are five right ways to do things.” That’s the flexibility and adaptability of technology, but the end result is what the project must be measured on from the start. – Tom Fisher, SAS

2. ‘Can you tell us a user story?’

I have found it helpful to ask such a client to write their expectations of the product/experience in the form of a user story. This accomplishes a couple of things that are of general utility in such a situation: It introduces the client to the formalism of defining a user story and forces them to be specific about their expectations. Further, it has the advantage of being directly incorporated into the development team’s agile process. – Bryan Smith, Myia Health

3. ‘What does success look like for you?’

Many of the stakeholders in a customer business are non-industry clients, such as economic buyers, procurement and infosec. The key question to each is, “What does success look like for you?” This teases out both desired benefits and potential risks, which are different for each stakeholder and should be addressed in their language and incorporated into the new or updated product. – Ivan Harris, Kraytix

4. ‘How can we make your job easier?’

In today’s employment landscape, most people are multitasking while tackling multiple job functions. Ask about their pain points, and then ask, “How can I make your job easier?” Then apply technologies that will work for them, not against them. By automating tasks and simplifying work through the right technology, the customer may find themselves with free time, and that’s priceless. – Ryan Decker, Marion Eye Centers & Optical

5. Are you willing to learn new tools?

All non-tech clients want to see their projects and developments run smoothly, but for that to happen, some of them might need to learn some additional tools. You have to know whether they are ready to make this effort right off the bat to manage your expectations and your knowledge of the future flow. – Daria Leshchenko, SupportYourApp Inc.

6. ‘How will you measure success?’

No “one” question gives the complete perspective of what the client needs. However, a good place to start is, “How will you measure your success?” A client who is looking to save cost versus someone who is looking to expand their customer base will have different technological needs. This question also helps to get the client focused on results and outcomes rather than the myriad technological choices that exist today. – Shashank Garg, Infocepts

7. ‘What user experiences do you want to offer?’

In the wireless industry, it is difficult for non-industry clients to understand the latest technologies available. When clients need in-building wireless solutions, we focus on solving problems instead of asking technology questions. For example, we ask, “What specific user experiences and digital services do you want to offer, and for how many individuals?” This helps us see the client’s vision for their tenants and venue so we can suggest the right solutions. – Julie Song, Advanced RF Technologies, Inc.

8. ‘Where do you want to be in six months?’

There are a few questions to ask based on the actual product, but ultimately, regardless of the product, you need to know the following: “Where do we want to be in six months, a year, or even five years from now? How do we want people to describe the product? How do we know we’ve won?” If we have a clear understanding of what constitutes success from the above questions, we ask, “What behaviors do we need to change with our customers/users?” – Edwin Huertas, Shockoe | Mobile by Design

9. ‘What do your business processes look like?’

When it comes to non-industry customers, the emphasis should be on the clients’ business processes. If experts in the industry do their due diligence to understand customers’ core processes and the scale of the project, regardless of the technology used, products can be successfully created. – Lana Vernovsky, Synoptek LLC

10. ‘How do you use automation?’

As an AIOps company, asking and understanding where our customers stand in their IT automation journey is critical to delivering the right tech for their needs. Whether it’s handling mundane IT monitoring so they can think more strategically or providing observability into their digital systems, their answer helps us to continue advancing their automation transformation. – Phil Tee, Moogsoft

11. ‘How do you envision your customer interacting with your product?’

The No. 1 question to ask to help understand a non-industry client’s tech needs is to have them describe (in their own view) their customer’s journey. A good way to phrase that is, “Please describe the product and how you envision the customer interacting with it.” From that, a technologist can gain an understanding of all of the components, touch points and data that need to be architected to deliver it. – Kim LaFleur, Title3Funds

12. ‘Who, what, when, where, why and how?”

The five W’s, as in the news, are always key. “Who, what, when, where and why” are all important, but also add, “How?” If you ask any client those questions about their new technology—as well as what they want from it—you’ll find yourself with a clear direction and understanding of their goals, setting yourself up to successfully create solutions and client loyalty. – Frank Speiser, Talla

13. ‘How can you accomplish what you want in the most pared-down version possible?’

It’s important to know that a client might think of a larger picture than necessary. There’s analysis paralysis, but there’s also scope and execution paralysis. There’s always the beginning of a success story, and the client needs to think of that so that the chances of failure are dramatically reduced. – WaiJe Coler, InfoTracer

14. ‘What’s your end goal?’

Ask your clients about their “big picture.” What’s their end goal? It’s easy to get bogged down in myriad project details. For technology to truly facilitate progression towards a client’s main objective, you have to take a step back, cut through the noise and hone in on the target results. See the forest through the trees, and it will guide you in the right direction. – Marc Fischer, Dogtown Media LLC

Data Storytelling skills are becoming a must-have for every data-driven organization. This unique skillset plays a critical role in marrying creative with analytical skills. Many organizations have begun to realize the importance of this role, yet they still struggle to define a skill set required to narrate stories with data.

Data Storytelling bridges the gap between numbers and actions, focusing on using data to make well-versed decisions.

The expertise of data storytelling is an ever-evolving field, however mastering the skills will not only provide you the necessary background needed to be successful but also help you pursue advanced concepts like user interface and user experience design, knowledge of data visualization, design thinking approach and more.

So what does it take to becoming a Data Storyteller? The below infographic illustrates important attributes and skills required for the role of Data Storytelling.

Interested in becoming a Data Storyteller? Check out our ebook, Guide to Becoming a Data Storyteller.

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