Gartner continues: “The forces combine to empower individuals as they interact with each other and their information through well-designed ubiquitous technology.”

That is an especially cogent point. No longer is the laptop a standalone piece of equipment, or the mobile phone, the social media network or even the big data back-end. All must work together seamlessly to provide a real-time computing experience that flows into our daily lives, informing us as we go.

We’ve redefined what IT means. That will become increasingly obvious in coming years. Mobile phones will become sources not only of text messages and apps, but of push alerts notifying you that you’re in the right place at the right time to meet an important new prospect, a way to automatically make wireless payments at coffee shops, even a way to remotely start your car.

These mission-critical activities reflect the true potential of the cloud, social data, big data and mobile working together. Businesses will spend $2.1 trillion on Third Platform technologies this year, according to IDC, because they realize that their competitive advantage depends on their ability to compute.

If you’re thinking about stepping onto the Third Platform yourself—and you should be—an easy way in is to look for cloud-based SaaS technologies that link together with social, mobile and big data, and with each other. Think of your computing devices not as standalone machines, but as puzzle pieces in a network. That will get you started in selecting the right set of providers, and establishing your own place inside of the Nexus of Forces.

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Thanks to data analytics, it just got easier than ever to attain managerial perfection (or something like it). Workers can refer to analytics systems as an automatic source of feedback, goals and transparent information. Managers can use analytics to decide when to delegate and how to react. If the practice of partnering with your data analytics becomes standard, the five major management mistakes below could become relics of the past.

1. Waiting Too Long to Give Feedback

One of the biggest mistakes that managers make is that they avoid giving feedback until the quarterly performance review, even if an employee is behaving in a way that might deter customers.

Data analytics solves the problem by making performance and benchmarks available to the entire team at any time. Employees can review their performance on an ongoing basis, and managers can point to analytics to illustrate how a certain behavior might be affecting an outcome. Rather than existing solely inside the manager’s brain, feedback has its basis in analytics that are available to everyone—and is thus easier to communicate and stay on top of.

2. Not Communicating Clear Goals

Many managers don’t provide their teams with clear goals. As a result, team members aren’t as productive as they could be, and there’s a lot of hit-or-miss in the process of getting things accomplished.

Through analytics, managers can set up benchmarks and objectives, and track each individual’s performance against them. Team and individual goals will always be clear, available and easily accessible in the cloud, even if those goals change. Data analytics act as a middleman to help employees prioritize which activities will get the team closer to each goal. By gauging their progress on a real-time basis, workers can continue to stay on top of their priorities.

3. Doing Everything Alone

“If you want something done right, do it yourself.” This is the mantra of some managers, who fear delegating work will lead to a lesser result. Data analytics help take the load off by making it clear who’s doing what. By seeing each employee’s tasks and progress in a single place, a manager can more easily look at her own task list and decide what to delegate to whom.

4. Delayed Reaction Time

Managers are busy people. Generally, they don’t have enough time to pinpoint every little problem before it grows and has a wider impact. Analytics can act as a departmental or team pulse, letting managers identify the health of their productivity, sales or other key indicators on a daily basis. With more data in front of you, fewer things can fall through the cracks.

5. Selective Communication

Ever find yourself telling different people different versions of the same story? Or accidentally leaving some people out of the loop entirely? That foments resentment, which every manager wants to avoid.

Data analytics can become a kind of informational water cooler, placing everyone on the same (web)page when it comes to team performance, gaps in achievement and progress towards goals. It’s a common data pool that tells the basic story that everyone can refer back to. Everyone will always feel ‘in the loop,’ at least to some extent.

Can you think of any other ways that data analytics can help a manager succeed, and help them avoid mistakes?

See Data Analytics in action by viewing our live, clickable Cloud BI Demo. 

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We just closed our latest round of funding. And that means we soon will deliver our on-demand business analytics service to customers throughout Brazil and Latin America — thanks to our new partner and investor, Brazilian software company TOTVS SA. You may not have heard of TOTVS, but it’s huge. In fact, it’s Latin America’s biggest software house (and sixth largest worldwide) that just so happens to be looking for a way to give its customer base easy access to business intelligence.

And that’s what brought GoodData to TOTVS’s attention: TOTVS will embed GoodData’s on-demand business intelligence service in its own software. That means companies throughout Brazil (TOTVS’s home country) and Latin America can easily turn their data into meaningful information, without the heavy-lifting other analytics tools require.

With GoodData, there’s no need for customers to understand, configure and manage complex big-data infrastructure — we do it for them in the cloud.  And because we’re in the cloud, customers can deploy GoodData in days (instead of months or years), with the security and scale companies demand — yet without the burden of buying and managing hardware and software. The result is immediate “time to value” as users quickly view find patterns, develop insight, and reveal the stories that will help their companies succeed.

That’s what our current customers love about GoodData. In just the first quarter of this year, we tripled revenue and added marquee customers including Comcast Cable, Lenovo, Switchfly and Universal McCann. Today, we have 20,000 active clients and 51 “PoweredBy” partners, which embed our on-demand business intelligence platform into their services. I’m excited to work with TOTVS to show customers in Brazil and the rest of Latin America how GoodData makes it easy for any user, in any size company, to turn data into insight they can immediately use.

With today’s Series D round for $22 million, TOTVS Ventures joins existing investors Andreessen Horowitz, General Catalyst Partners, Next World Capital and Tenaya Capital, which also participated. This marks TOTVS Ventures’s first strategic investment outside of Brazil.

At GoodData, we never stop. This newest funding will allow to extend the technology innovations our customers have come to expect from us. It also sets us on the next leg of our journey to become the global leader of business intelligence in the cloud. As I said, it’s another great day for GoodData. I extend a giant thank you to all our customers, employees and partners for making this journey possible.

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A Dramedy of Errors

Sometimes the frustration with Excel reporting reads like a scene from NBC’s The Office. But in most cases it’s completely frustrating without any laughter at all. The reality is that as spreadsheets and databases grow in complexity, the more errors are present with each new Excel report. In fact, roughly 88% of all business-specific Excel documents contain errors In a funny turn of events, a University of Massachusetts graduate student exposed errors in Harvard economists’ Carmen Reinhart’s and Kenneth Rogoff’s spreadsheets.

Excel Errors Flow Upstream

When developing reports in the Excel environment, it’s tempting to believe that the buck stops with you. That is, no one else will – or at least very few people – will be affected by errors in your Excel reports. The opposite is actually true. In the business environment these mistakes tend to flow upstream. This is usually fueled by half-baked data that is sent up the channel to C-level executives who then make decisions based on incorrect, or insufficient data. Then this trickles back down stream to analysts, marketing professionals and sales professionals as they make smart decisions with the wrong data.

Why Your Data Needs to be Perfect

The bottom line is that no one can make smart financial decisions within your organization if all they have to go on is flawed data. No matter how smart or talented your financial team is, if they are dealing with error-filled Excel reports, any  smart decision that is made will never be all that smart. All of this needs to be taken into account as you consider the pros and cons of Excel, and how it fits your big picture plan for business growth and financial sustainability. In the business world, little mistakes soon balloon into larger, regrettable mistakes.

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Corporate training used to be a lot harder than it is today.Trainers would build PowerPoint presentations and deliver course content live and in person. There was no way to track the success of each course. Trainers would guess at how many people had absorbed information. Some have told me that they thought the vast majority of their training was wasted, and they didn’t know how correlate training with business impact.

E-Learning Saves the Day, Sort Of

Several years ago, on-demand learning emerged as a promising new solution. Rather than hiring a team of trainers to teach the same courses, businesses could scale their existing programs while maintaining consistency and cost-effectiveness. Still, trainers faced hurdles. The process of transforming live material into an on-demand learning program often took weeks as they learned how to use new software. And trainers still weren’t sure if the material was actually effective.

Taking Training One Step Further

The answer was to simplify course creation and management, and also install analytics that enabled trainers to track the success of their courses. With Mindflash, businesses can upload their existing files—from PowerPoints to audio and video files—organize them using a simple course dashboard, add quizzes and publish to the Web. The follow-up labor, which includes sending out invitations and reminders, issuing and grading quizzes, and post-class surveys, is automated.

Trainers found themselves with more time to create quality courses, but there was still the guesswork about how much students had actually learned. We partnered with GoodData (through our joint partner Keboola) to take care of that piece. In the process, we’ve learned a few things about how analytics can optimize the experience of training and designing coursework.

1. Trainers can continually assess absorption of all of their global courses. GoodData-powered reports will, for example, let trainers see, by percentage how many people got which questions right. If 60 percent of people are getting Question #2 correct, for example, and only 10 percent are nailing Question #3, there might be something wrong with the phrasing of the question itself, or it isn’t being covered well in training.
2. Trainers can iterate their programs to maximize results. Mindflash builds surveys into each course. Trainees give feedback on completion of each course, and GoodData will display that information in a quantitative form, giving trainers a birds-eye view of where each course is working and where it isn’t.
3. Companies can correlate how their training programs impact their business. Our customers have been able to correlate completion of courses with an increase in productivity and decrease in cost, sometimes of two- to four times. Kofax, for example, reduced their training costs by 80 percent using Mindflash. By focusing on the most effective coursework, businesses can, in turn, generate the best ROI.

Analytics: It’s Just the Beginning

Analytics enable companies to both optimize individual courses and find the true business impact of training programs. This is a sea change in an industry that used to be notoriously hard to measure. As e-learning evolves, we’re excited to see where analytics will take us next.

For a more in-depth overview of how Mindflash partnered with GoodData, see the case study. To learn more about Mindflash or set up a free trial, visit their website.

Like this post? Check out related blog, Big Data and the Big Opportunity to Reform Education.

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1. Pacing. This type of analysis helps you measure progress against goals. These goals can be based on historical data, industry benchmarks or user defined. The important thing to remember is that progress isn’t necessarily linear. For example, some organizations close 50 percent of their total bookings on the last day of the quarter. Others, plateau towards the end. You need a way of understanding how you’ve done historically (or how your competitors are doing) and measure your current progress against that. Pacing analysis gives you a big-picture overview of your trajectory and progress against goals.

2. Parts of whole reporting. This will help you understand the moving parts that are helping you reach your goals. If you’re on target for bookings for the quarter, you’ll be able to see which product lines, sales reps, campaigns or other assets are contributing most to that. If, on the other hand, you’re behind, you’ll be able to pinpoint the cause.

3. Scenario analysis. When faced with a big decision, it often makes sense to consider a worst-case scenario, a best-case scenario and the most likely scenario. This is what scenario analysis does for you. It projects possible future outcomes. You’ll get a view of how these outcomes might occur, for example, if your biggest client has a bad quarter, they might cut out your services to save money, or they might rely even more on you in order to focus on their core competencies. Most likely, they’ll have an okay quarter and nothing will change.

4. Cohort analysis. Also known as segmentation, this marketing-analysis technique lets you see how people engage with your content or product over time. Say you roll out different versions of your website, and you want to understand how much your millennial audience engaged with the new site versus the old one. Cohort analysis will tell you that. It’s the way to see different usage patterns and the evolution of usage over time.

5. Correlation. The classic question in this category: what’s the correlation between diapers and beer? The answer is that when a dad goes to the store to pick up diapers, often times he’ll pick up a six-pack. So diaper sales are positively correlated with beer sales. Correlation analysis can help you find these types of unexpected relationships.

Once you have these 5 business analysis techniques in your toolbox, you’ll be able to cover a lot of analytical ground—and have the information you need to make more informed decisions as a result.

Need help crafting your business analysis strategy? Contact Us.

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Enter GoodData for Yammer, which will show you any trend you want, when you want to see it.

In partnership with Kanjoya, the leading platform for emotional engagement, GoodData combines your operational reporting and emotional sentiment in the same dashboard, providing full context on the structured and unstructured data in your Yammer networks.

We’ve built GoodData for Yammer around best practices and KPIs for measuring internal and external Yammer networks, enabling the measuring and scoring of everything from the big-picture health of your network to individual posts:

• Highlight key trends and topics in your network, groups and even individual posts.
• Perform ad-hoc analysis on key data in Yammer networks (internal and external) around users, groups and Yams.
• Ensure you’re making the most out of your ESN by tracking and analyzing internal Yammer usage and adoption.
• Pit historical trends against current data to see the health of your user base and group activity trends. For example, you can track engagement this quarter, versus previous quarters versus all-time to see how usage patterns are changing and to measure the effect of any programs or campaigns.
  
• Receive text and email alerts if your metrics demand immediate attention.
• Gain a complete overview of your social investments by adding additional data sources, including Facebook, Twitter, Google+, Enterprise Social Networks (ESNs), CRM and other internal data sources.

The Wisdom of the Cloud

GoodData for Yammer is actually an application built on top of GoodData’s leading business intelligence (BI) platform. Thanks to our cloud-based architecture, GoodData scales to accommodate Big Data and easily connects into all types of data sources (cloud-based or on-prem).  This openness allows us to integrate with leading technology companies like Kanjoya, for example, which uses their natural language processing (NLP) engine to provide rich sentiment and emotion scoring for all Yams in the GoodData for Yammer application. Moreover, because all data is on the cloud, it is more secure. (To learn why, read this.)

In short, the cloud is enabling the new era of BI. For the first time ever, it is easy to collaborate with other platforms to compile, analyze and score disparate information sources. Users on any device can see and interact this information in an intuitive visual form, gaining insight on exactly where to improve their business. That capability, more than anything before it, will truly enable you to see the ROI of your network.

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Executives ignore this development at their own peril. Data skills are a key component to growing a business, keeping an organization healthy and even, increasingly, climbing the career ladder. In the not-too-distant future, those without analytics abilities will be left behind.

The good news is that regardless of specialization, there are a handful of general ways that any executive can apply data analytics to improve their results and job performance. Here are the five most common ones:

1. Justify the Need for Resources and Prove ROI

Need more staff or budget? Data analytics is one of the best ways to prove your need to other stakeholders. By using analytics to monitor and evaluate your part of the organization, you can draw conclusions about which activities are driving the most results, inside and outside of your department.

Historical data can show you what activities bring the most ROI, and therefore should be supported most. If you’re in sales, for example, you might discover that most of your closed sales started with happy hour meetings, so you could grow your happy hour budget. You can also compare historical and current data to find weak spots—and make the case that you need to build your bench to fill them in.

2. Plan for the Future

Scenario analysis built on models, forecasts and other types of data can help you understand the most likely outcomes of decisions. Predictive analytics can help you identify the most likely scenarios for hiring, capacity planning, budgets, equipment needs and other considerations. Instead of relying on guesswork and near-term intuition, actively plan for the future.

3. Recruit the Right People

Hiring managers have long understood that the best resume doesn’t necessarily make for the best worker. Data analytics are already helping fill the gap between a fancy resume and the right characteristics. Large national retailers, for example, have a huge hiring burden, according to The Economist. A retailer might have 1 million employees and an annual attrition rate of 50%, meaning the company must hire 500,000 people per year. They’re using data analytics to look beyond resumes and applications to pinpoint the important habits that make the best employees. The Economist named a couple of unexpected correlations:

• People who deliberately install a browser, such as Chrome, rather than using their machine’s default browser are assumed to make better employees, perhaps because they’re proactive.

• For certain jobs, such as call center support, people with criminal records tend to perform better than those without.

Data analytics, in other words, adds new richness to the hiring of new workers.

4. Compensate and Reward Your Employees

Data can also simplify the process of identifying the best performers. Data brings a new level of granularity to the process. You might already know who your best closers are, but data might point to the person most responsible for filling the pipeline. If one of your helpdesk staff has the ability to answer her tickets the first time, she has a bigger impact on the business, because she’s not only more efficient than other workers, but is sending a positive brand association through every thorough answer. With data analytics, pinpointing such performers becomes easy, and it’s also possible to calculate financial rewards based on the real impact they have on the business.

5. Make the Right Decisions at the Right Time

Data analytics bolsters the probability of delivering the right service or information at the right time. Is it the right time to give your star performer a raise? Do you want to include an add-on service for that prospect you’re pitching, and should you contact them on Tuesday or Wednesday? What specific information should you include in your campaign geared at retired tech CEOs living in San Luis Obispo? Data analytics are important not just for giving you the right information, but for enabling you to execute at the best possible time.

All in all, big data analytics are your friend. Use them wisely and use them well. Also know that not all data analytics platforms are created equal—if it’s too complicated to understand, consider finding a platform that you can work with.

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Ask for a demo to see how GoodData can help you turn your data into a source of profit and competitive advantage.

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Where Did Dashboard Reporting Come From?

Historically, business intelligence (BI) tools were designed for data specialists who would build customized reports using a complicated UI. These specialists generally had PhDs in data science, and they needed that kind of training to discern the information that their systems were spitting back out at them. At the time, BI had no dashboards, so data came in the form of a spreadsheet, and the data scientist had to draw correlations and conclusions from columns of numbers. Then, the specialists would build and compile individual reports.

Thanks to cloud and advances in technology, the concept of dashboard emerged. People realized that it’s important to have all pertinent business data in one place. That way, you can see the context of your data and track multiple KPIs next to each other. Finally, there was a visual way to consume and interpret data and make better decisions. Using dashboards, even those of us who aren’t data scientists could understand our businesses better.

How Dashboards Evolved

In the early days of dashboards, however, you still had to build your BI environment by yourself. Reporting tools like key performance indicators (KPIs) had to be constructed by the data scientist before they were put in the dashboard. So dashboarding was either a module or an add-on.

Today, dashboarding has become much easier. Although some BI solutions are still siloed, the newest wave of solutions lets you build, edit and move dashboards around with the same ease that you can move around, say, PowerPoint or Keynote slides. Still, not all dashboards are created equal.

What to Look For in Dashboard Reporting

In order to make sure you choose the right dashboard, you should look for three things:

1. Context on one screen

In traditional BI solutions, you have to navigate to another screen to build your reports before placing them on a dashboard. These separate environments create a psychological divide that makes it more difficult for users to orient themselves in the dashboard and understand the data models they’re building. If you create your report in a separate page, it’s hard to imagine what a chart will look like when it’s finished and put on a dashboard next to other charts, tables or images.

The trick is to find a solution that lets you have all of your context in one place. You’re never forced to go anywhere else. Everything is integrated and in one location. There is no divide between the dashboard and data analysis. Because you know where everything is at all times, your data doesn’t live in a vacuum. You can even find new insights by seeing charts side-by-side, and moving them around.

2. The ability to move things around

Building and moving KPIs around on your dashboard should be as easy as it is to do things on a mobile device—swipe, zoom, shrink, click on a dialog box to see something in detail. That way, you can still have your context all around your actions, so you don’t get lost in your data or confused by what you’re seeing. You can position everything perfectly, adjust the layers of your dashboard and edit it, without losing your context or the clean look and feel of your dashboard’s design.

3. Get information when, where and how you need it

In today’s real-time business environment, daily or weekly updates don’t cut the butter anymore. You should be able to get updates on demand, when and where you need them. Your mobile device should also be able to push you notifications — informing you that you just received a much-anticipated email, for example—to further simplify your decision-making. Your BI should be waiting on you, not the opposite.

To learn more about dashboards, visit our What is a Dashboard blog.
Request a demo to see how GoodData’s dashboards can provide an integrated view into your business performance to help you make faster, better decisions.

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By using a dashboard, you can more easily process the meaning of the information your BI system is giving you, and make better decisions as a result. Everyone from the CEO to middle managers can use dashboards to see information when they need it. As a result, these workers can make changes in real time, rather than using guesswork or monthly reports.

As the above image shows, dashboards and other visual BI features should all fit onto one computer screen. You see all the most important graphics in one place, and you can drill further into any visual on the dashboard as needed. That means clicking on the visual and changing your date ranges, reduce the number of data points or hone in on certain categories, like a product or team. That way, you can find out why, for example, a business unit is performing as it is.

Benefits of a Dashboard

There are zettabytes of data in the world today, and companies are drowning in information. A dashboard places the data the companies need in a visual, easy-to-understand format. The ability to see the data that you need, when you need it, gives you the ability to quickly understand your company’s situation at any given point in time. Rather than digging through emails and Excel spreadsheet, you can consult your dashboard for a quick insight.

A dashboard democratizes access to big data, so that anyone in any department can have the right information at their fingertips. It removes the need for a specialized data scientist for every simple question. Dashboards are an important tool not only for internal company operations, but for communicating with clients. We’ve heard time and again that dashboards have saved our clients hours in terms of compiling reports and sharing information.

Types of Dashboards

Dashboards are customizable depending on your type of industry and unique needs. The range of customization goes from the appearance of the dashboard [are pure graphics best or do you prefer spreadsheet-like reports] to the type of data on display. A retailer might choose to display daily sales by country on their dashboard, for instance, while an IT service provider might gauge network speed and customer complaints. Specifically, dashboards can be customized in several ways, all of which can work together to best suit your organization:

1. By decision-making horizon

A strategic dashboard provides a general overview of how an organization is performing. It depicts overarching, longer-term trends, such as sales so far this quarter, ongoing costs, etc. You can use the strategic dashboard to gauge the health of your overall company and ensure that you don’t have any leaks in your bucket, so to speak. In general, strategic dashboards are used for quarterly assessments.

A tactical dashboard is used to analyze trends in your business. It’s common to look for trends over time, for example, did you sell as many widgets this month as you did last month? What about the same month a year ago? Tactical dashboards center on historical data, giving an overview that enables you to discover important trends.

An operational dashboard helps a company optimize its operations. Used for customer- and partner-facing activities, operational dashboards provide information to company representatives that they can use to interact and transact more effectively. For example, an operational dashboard will show a customer service rep a caller’s payment history, contact information, troubleshooting history and any other records of interest.

You can use an operational  dashboard for real-time, ongoing information, so that you can make immediate decisions. For example, you can see the health of your call center—how many lines are open, average wait times—on a second-by-second basis, so that you can address emergencies or bottlenecks as needed. This type of real-time dashboard is also ideal for generating ‘push’ notifications on your mobile device. If your BI platform notices that you happen to be eating lunch near a sales prospect, your phone can notify you of the opportunity in real time.

2. By function

You can have a dashboard that is specifically designed for sales, marketing, customer engagement or customer support. In these dashboards, you can set goals and milestones, as well as competitive information, and gauge your progress over time.

3. By type of analysis

There are three main types of analysis that a dashboard provides: reporting, analytics and ad-hoc. Dashboard reporting refers to the general metrics that appear on the dashboard—the charts, tables, graphs, etc. It tells you the what is being reported on, such as sales quotas, and the numbers associated with that item.

Analytic reporting goes deeper. To extend the sales quota example: What did your top performers do to exceed their quotas, and why haven’t your bottom performers been improving? Analytics are where the insights live. You can find the specific sources, no matter how granular, of your problems. Then you can adjust your dashboard, perhaps by setting new milestones, and try out a new strategy to see how that works.

An ad-hoc dashboard is what you get when you want to do a customized analysis that doesn’t come in your pre-packaged analytics. In ad-hoc analysis, you put in custom metrics (how many dog-owner salespeople do I have, and are the dogs the reason they’re performing better?) It is a customized dashboard that offers you flexibility in terms of how you analyze data. The downside is that different users may customize an ad-hoc dashboard in different ways, gaining different answers to the same question.

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