Qlik Business Intelligence and Analytics

Digital transformation is reshaping businesses and industries in many ways. The Internet of Things (IoT) is a great example of this. There's a lot of talk lately about IoT data, but this tends to focus more on what's used to capture the data - such as wearables, sensors, iBeacons, and other network-connected machines. Gartner believe that by 2020 there will be 25 billion connected things with adoption across all industry sectors, while data will double every two years due to the vast amount of data created by IoT.  However, the real value of the Internet of Things goes beyond connected devices. The greatest value for organisations comes from combining the data generated by these devices with other customer or operational data to uncover insights and establish predictive models. This is where business intelligence platforms like Qlik, come to the fore.  This is the exciting promise of IoT, but without the ability to link data from the smart, networked “things” with other business data, its value is limited.

So how would a business use IoT data?

IoT technology has many potential applications for businesses.  For example, package delivery trucks, manufacturing systems and electrical grids all typically have sensors to monitor performance. Retailers can combine data gathered from in-store iBeacons with customer transaction histories and store behavioural models to determine the best promotion to send or other actions to take, such as notifying the store staff that a VIP has arrived.  More and more companies are now starting to collect and store data from such sensors. The next step is to analyse the data. Looking for patterns in the data could illuminate ways to improve business operations, such as doing more preventive maintenance or designing more efficient delivery routes. 

Collecting and analysing data from the Internet of Things is different from doing it in mobile and web enterprise systems – because the data isn’t located in resource-rich data centres. Instead, it’s out there in the real world. IoT data usually consists of custom log files, is sometimes misnamed, and appears unstructured. In fact, IoT data has structure, but it isn’t in a traditional relational or other standard format. The log file structures and included data points vary from manufacturer to manufacturer, model to model, software version to software version or even company to company. This introduces complexity when interpreting the data and trying to format, normalise, and combine it with other relevant data for analysis or operational systems. Without tools like Qlik to help interpret IoT data, the time and effort to put the IoT data to work is costly, time consuming, and prone to manual error.

What does IoT mean for the CIO?

The IoT will create unprecedented opportunities and challenges for every CIO in every industry. Three main things that have changed in recent years are accelerating the number and value of connected things:

• The cost of connectivity and embedded technology is no longer a barrier to adoption with broadband, Wi-Fi, Near Field Communication (NFC), Bluetooth and mobile networks now able to support large volumes of IoT connectivity at little incremental cost.
• The IoT's complexity and intelligence are evolving to support an ever-broadening range of use cases.
• The provision of information via sensors and the resulting analytical opportunities and context-setting are transforming how we look at the world and at ourselves. Data is inherent within the operations of things, making them a rich source of further insight. Through analysis, the data collected from things can turn into information. The information captured and distributed by the IoT is a key source for the new digital strategies.

How to realise business value from IoT data?

Gartner research into the IoT in April last year showed that 29% of organisations have already implemented the IoT, and that another 14% are planning to implement the IoT in 2016. This indicates that the technology will be solidly in early mainstream business adoption by 2017. The first step is to move the conversation from talking about IoT, to talking about what IoT can do, or be, specific to your organisation. Organisations also need to look at IoT in conjunction with other technologies. In order to fully realise the value of combining IoT data and other enterprise data in an agile way, organisations must leverage modern business analytics tools to accelerate and automate the processes. Using tools to profile data, intelligently discover its structure, and then automatically parse and combine it with other relevant enterprise data on an ongoing basis makes the IoT data more accessible. This creates an infrastructure for ongoing expansion and evolution in the use of IoT data to understand customers and create predictive models for operational systems.

The shift now is toward externally focused benefits with IoT with improving customer experience as the hottest, most rapidly growing and most common benefit being pursued.  The IoT is increasingly becoming a competitive weapon in the marketplace. IoT is lowering costs, increasing functionality, and addressing issues in usability, interoperability and openness. Usability is not just for end-users, but also extends to developers building solutions.

There are many best practice use cases for using IoT data already, here are some examples:

• Retail Store Beacons - If customers have opted-in on their mobile devices, then beacons in branch retail stores can greet the customers when they arrive, keep track of loyalty points, push recommendations based on customers' purchase history as well as current interactions, and enable customers to pay through their mobile devices. Target in the USA is doing just that. Amazon Go  and it's no lines, no checkout concept is another example here.
• Preventative Diagnostic Care Monitoring & Smart Medication - In healthcare connected devices can transmit patient conditions and information to healthcare providers to promote self-care and detect problems early, thereby reducing doctor visits. While smart pill bottles combine sensors with mobile technology to alert patients to take medication, and notify healthcare providers if bottles are not opened. Phone calls or text messages alert patients as an additional reminder for improved patient compliance. Smart pills with embedded microsensors connect to patient skin patches to track ingestion and gather health data for patients and physicians.
• Digital Oil field management - Austral Pacific Energy are using down-hole sensor data to populate distributed control systems to manage the oil extraction process for assets that are difficult to recover, such as waxy petroleum, which requires heat injection.
• Smart irrigation - Councils and agriculatural companies are looking at smart irrigation for urban parks or crops that can be centrally controlled using ground sensors to indicate if and when irrigation is needed, thereby saving water.  Stirling in Australia are a case in point here. 
• Pre-emptive maintenance - Manufacturing companies and energy providers are using sensors on industrial equipment to gather operational data for analysis to predict and prevent failure, and to support improved maintenance. Read our article on using analytics for pre-emptive asset management in the oil and gas industry.
• Asset optimisation - Real-time data collection from industrial assets, such as refrigeration systems, to assess operational performance and improve efficiency. It is used in oil and gas, utilities, manufacturing, refrigeration, and power distribution industries.

If you have the data and the detail, you need to understand how your data is associated or related.  If the sensors in your supply chain indicates a shipment is going to be late, aren’t you going to want to let your customer know the shipment to the store will be delayed?  Qlik offers a platform that provides the ability to pull data from multiple sources, at a detailed level, and its core technology associates the data providing a roadmap to discoveries for the business user at head office or out in the field.  This level of data visualisation will be crucial as companies continue to digitise and extend to IoT services.

In early adoption phases it is easy to spend significant time and money on trials and deployments that produce little to no value. Estimating the strategic value of IoT use cases can help CIOs avoid wasting resources on unproductive use cases, or avoid forming partnerships that don't deliver results. 

Many organisations have invested in Infor M3 ERP systems - previously known as Lawson - to streamline financial and operational processes across their businesses. While Infor M3 is recognised as best-in-class, it can sometimes struggle with business intelligence (BI) - especially when integrating with non-Lawson third-party systems. We frequently hear Infor M3 users talk about the difficulty of accessing and analysing their M3 data with or without in-built BI systems, with reports that only take users part-way to the insights they need.

Built for centralised reporting, Infor M3 and most add-on BI tools lack the flexibility to meet new reporting and analysis demands. This is especially true when requirements include combining M3 data with information from other sources and when large data volumes cripple performance. The inherent complexities, lack of speed and usability, and time-intensive nature of these approaches for reporting, hinders executives and analysts from improving decision-making and business performance. As a result, M3 users can often lack visibility into their business processes and critical insights that remain hidden away inside the system.  

Inside Info's Director and Qlik Managing Consultant, Phil Langdale, is speaking at the Infor M3 Users Network (IMUN) annual conference, held on the Gold Coast on 17-19 May 2017, about how to use analytics to reshape the entire organisation for those running Infor M3. In particular, Phil will discuss how many of our other clients who are running Infor M3 are using the leading Qlik business intelligence platform to transform operations and deliver interactive, on-demand analysis and dashboards for Infor M3 and other data, delivered in just a few weeks.

Rethinking Information Needs

The growing need for broader data literacy among executives and business teams requires a rethink of how information needs are addressed within organisations. For those businesses running Infor M3, that means rethinking how to better leverage M3 and other data to provide self-service intuitive dashboards and analytics that engage all types of users - from executives to analysts and operational team members. When used correctly, key insights can be delivered quickly and provide a consolidated, consistent view of performance across the enterprise for more effective, agile decision making.

The Inside Infor M3 BI Dashboard

In particular, our experiences with Infor M3/Lawson have allowed us to develop the Inside Infor M3 Dashboard - a proven, best-practice business application developed by our senior consultants. Already used by firms like GWA and Manassen Foods, the solution delivers extraordinarily sophisticated interactive analysis and a consolidated view of performance, through analysis that is highly visual and affordable, and quick and easy to deploy, use and change.

"When I first saw what Inside Info could do with Qlik and our data, I was immediately impressed. Qlik provides our brand, sales, management and operational teams with complete transparency," says Wayne McIntosh, Finance Director, Manassen Foods.

The Inside Infor M3 Dashboard significantly fast tracks BI projects and increases user adoption by leveraging off the learnings of others, with customers typically up and running in about 30 days. This dashboard - based on the Qlik business intelligence platform, provides a:

• One-screen view of all the facts: Consolidating data from Infor M3 and other sources to ensure cross-functional visibility, providing a clear view of sales, inventory, service levels, customers, financial and other operational performance. A number of filters allow you to understand key measures against budget over any time period, and conduct comparative analysis. Additionally, the solution allows linking of transactional processes, dramatically improving business strategies and uncovering opportunities.
• Consolidated view across multiple businesses and divisions: The dashboard provides a single view of financial and operational performance across companies within a group or individual business areas - often difficult to achieve with other BI tools given multiple and varied data sources - and drill-down access to any area of the business. 
• Near real-time visibility into operations: Instead of out-of-date reports, the dashboard offers on-demand self-serve analysis of data, often replacing hundreds of OLAP-based reports and empowering users to perform their own analysis, reducing IT support by up to 90 per cent. Users report 54% less time accessing information and 51% less time analysing it, according to IDC.
• Rapid response times: Sub-second query response on very large data volumes - into the hundreds of million records - without losing transactional level detail, with data refreshing as often as your underlying source systems.
• Comprehensive views with granular detail: Ability to view information at a detailed, transactional-level, and anywhere in between in any path decided by the user, with no pre-defined drill-down paths. If you've got a business question, odds are you'll be able to answer it without having to wait for another report. Easy consolidation of data from any and multiple data sources.
• Simple to use, available everywhere: Access your dashboard from any device - whether this be laptop, tablet, a web browser or your mobile device, with HTML5 compliance ensuring a consistent experience on each.
• Very fast implementation cycles:  A typical project lasts 30 days and is 53 per cent of the total cost of other BI solutions, according to IDC. Meanwhile, adding in a new data source or building a new view of the data can be modified very easily within a few hours.

To understand more about how Inside Info can help organisations make the most of their Infor M3 and other data, check out this Manassen Foods case study below.

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Depending on the role, different people in a company typically have different reporting and analytics needs. Whether you’re building a business intelligence dashboard  for the executive team or an operational team, do your dashboards tell the story you want to get across or does the insight get lost in a sea of KPI’s?  Here are a few tips to keep in mind when designing and building great dashboards. 

1. What story are you telling?

As with any communication, the first golden rule is to understand who it is you’re trying to persuade, inform and engage with your dashboard.  Once you understand this group and how they consume different types of information, storytelling then becomes an important skill.  Humans have long been engaged in storytelling, it’s one of the cornerstones of communication. In fact, stories are remembered up to 22 times more than facts alone. With that in mind, taking a structured narrative approach to your business data can help make it more understandable, memorable and persuasive.

By assembling your data into a story, it creates cohesiveness and structure for presenting that data. The most engaging stories are conversations, giving listeners room to ask questions, just like an interactive data visualization.  So being able to share your insight with others is a priority. Dresner’s Collective Insights Report last year found that collaborative BI has become a necessity while Aberdeen found it also can drive an impressive 18% more revenue growth in organisations.  Our article on how to foster a collaborative analytics environment explores this further.

Qlik Sense’s unique data storytelling capability fosters collaborative business intelligence allowing you to move seamlessly between presentation mode and the original data set to answer questions on the fly, while its powerful visualisations support the narrative. 

2. Choosing and displaying the right metrics

Excess information, confusing graphics and unnecessary features can make a dashboard difficult to use and understand. You should “remove everything you can and nothing else”.  If you have only one minute before a dashboard must be completed, ask yourself what to remove—not what’s missing. This will give you a good feel to what should be included in the application. Always remember to take it back to your audience and who are the main users of the dashboard and the metrics they want to be able to view easily and quickly. Smart search capabilities built into the dashboard can also connect the dots between data making it easier to find answers.

By incorporating data visualizations into your dashboards complex data can become clearer to see trends and correlations that aren’t visible in rows and columns. There are some guidelines however to best practice.  Be careful not to overdo your use of colour, while universal colours like red and green if used should convey good or bad performance in graphs. Keep your dashboard design simple by limiting the number of KPI’s in a dashboard to 9 or less and avoid visual clutter.   Choose the right chart for the right purpose.  For example, pie charts are good for comparing parts of a whole on a limited data set, while scatter plots are great for analysing product performance or margins to see any outliers that need attention.

Qlik’s simple drag-and-drop interface and smart visualizations use new techniques that make it easy to convey meaning in data.  Each chart is fully interactive, one click from summarised to transactional level detail, while visualizations dynamically update to changes made anywhere in the app.  Each chart is also a responsive design, automatically adjusting to screen size and mobile touch.

Incorporating mapping and location intelligence may be important for certain dashboards if looking at different channels, suppliers, client or product dispersion.  It becomes another tool to display and navigate insights.  If this is important, check out Dresner’s new study on location intelligence.

Remember design is not just what it looks like and feels like.  Design is how it works.

3. Responsive Design & easy to manage

A good dashboard isn’t a one-size-fits-all approach.  That means, if delivering a dashboard for a mobile deployment is required, the BI software needs to be smart enough to automatically re-render its design to best fit the deployment. If not, it becomes a costly exercise in building the same dashboard for a server deployment, then a mobile deployment, as simply shrinking a desktop version of a dashboard to an Ipad isn’t a great user experience in terms of functionality and form. So look for business intelligence platforms that can provide access on any device, anytime, automatically adapting to the device, being  HTML5 compliant.

Ensuring the dashboard is easy to use is a given, but being easy to manage is also important.  There needs to be strong data governance built behind each dashboard, so everyone is still working from a single version of the truth.  This may take the form of inbuilt security or leveraging governed data libraries of data models, applications, data definitions and data stores.  This ensures scalability as your organisation grows, especially if leveraging self-service BI applications. 

4. Automate Data Integration & Consolidation

According to IDC the average employee spends over six hours each week on data-gathering, compared to just over four hours on consolidation and analysis. Minimising this time by making it easy for employees to access relevant data in a timely manner must be a priority for firms looking to maximise productivity & reduce unnecessary costs.  Because data collection has traditionally been a manual process, even when traditional BI tools are in play, it has been both slow and labour intensive. System and data integration are often cited as the main limitations of current BI systems or processes.

However, sophisticated BI tools like Qlik Sense software have upended this paradigm, providing point-and-click data integration from any and multiple data sources, while business users have the option to create their own powerful dashboards and analysis simply on the fly - or to use guided dashboards created by IT. Each, however, allows for full, drill-down capability from a summarised view of data to transactional level detail, quickly and easily on a consolidated view of data across the enterprise.

The value of self-service analytics over outsourced methods cannot be overstated. Forbes found that close to 90% of industry leaders - more inclined to use this distributed BI framework - report seeing significant business benefits from their BI software. This is in stark contrast to organisations overall, where only 53% have the same positive view.

If you want to know more about Qlik and how it can help you create simple, intuitive and powerful dashboards, view the ebook below.

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Gartner just released the 2017 edition of its Business Intelligence and Analytics Platforms Magic Quadrant Report, a rundown of the industry that's eagerly anticipated each year by insiders in business intelligence.

As we mentioned in our earlier blog post about the 2017 Gartner BI Magic Quadrant, Qlik was named an industry leader for a record-breaking seventh consecutive year this year due to its above average customer experience, robust product range and strong partner network. Qlik Sense is the fastest growing BI product in the market, and for good reason. The solution had a very strong 2016, beating revenue expectations with strong customer growth. Moreover, it's plain to see that Qlik's move to a private company has helped drive more investment into product development and innovation.

But the release of the Magic Quadrant also gives us a chance to look more broadly at the marketplace for business intelligence and analytics. The report also highlights key trends within the business intelligence and analytics market and what businesses should consider when looking to invest within these areas.

Modern BI will continue to dominate

The increased need for data governance within enterprises will continue to drive the need for IT involvement in user-led BI deployments. As BI engagements continue to grow in terms of number of users, data complexity and use cases this will ensure that self-service BI platforms must also provide strong data governance layers. According to Gartner modern BI tools that can support greater accessibility, agility and analytical insight while also maintaining ease of use (but at enterprise scale and trust for complex and large datasets) will drive and dominate new buying. While embedding analytics within applications will continue to enhance services to customers, users and clients and be a key enabler of more pervasive adoption of, and value from, analytics.

Smart data discovery and advanced analytics

It's well acknowledged that Qlik pioneered Data Discovery BI - user-driven, self-serve analysis of data that is easy to use, easy to change and can be delivered quickly. Gartner talk about this concept evolving even further to develop advanced analytics and further insight for business users. So how does Qlik handle this? Qlik's engine works as people think, it intuitively seeks to understand all the possible associations that exist in user's data, across all their data sources and allows them to freely explore that data, asking questions in any direction without restrictions or boundaries. That means no predefining data hierarchies or building data cubes. In short it facilitates what many investments in neural networks are striving to achieve. Qlik enables a unique search experience, associative data prep and profiling, data enrichments, suggestions, labeling, compression, truly smart and adaptive visualisation, and indexing across big data sources. In short it defines 'smart' from data preparation, to finding patterns in data, to sharing and operationalising findings.

Moving towards an AI-powered future

We've already seen a lot of growth in the BI market, but what's coming next might be truly groundbreaking - in the near future, business might be powered largely by artificial intelligence (AI). In fact, Gartner anticipates that by 2020, 90 per cent of BI platforms will be powered by such features as natural language generation and AI.  Gartner refers to this movement as a "modern wave of disruption," and it's coming slowly but surely.

To read more about Gartner's report, download a complimentary version of Gartner's 2017 Business Intelligence and Analytics Platforms Magic Quadrant below.

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Last week Gartner released the 2017 edition of its "Business Intelligence and Analytics Platforms Magic Quadrant Report," which details the latest developments in business intelligence and compares BI platforms in terms of vision and ability to execute on that vision, for those looking to invest in these type of systems.

To download a complimentary copy of Gartner's BI & Analytics Magic Quadrant Report click here.

Inside Info started delivering Qlik solutions to Australia over fourteen years ago. We did so because of a firm belief that Qlik's strategy, product vision and capabilities provided a well-needed alternative to traditional BI platforms. Qlik defined Data Discovery, led the decentralization of traditional BI to empower business users and established true, governed, self-serve analytics that can be delivered quickly. There are a few reasons why Qlik remains only one of three BI Leaders in Gartner's recent BI Magic Quadrant report.

A leading role in the BI industry

First and foremost, it's clear from Gartner's business intelligence research that Qlik is one of the leading players on the BI playing field, and it's been in that role for a long time. The Magic Quadrant listed Qlik as one of the industry leaders for a record-setting seventh year in a row. It also named Qlik Sense as one of the fastest growing products in the market, with a strong 2016 recording revenues that exceeded all expectations.

Customer experience

Gartner positioned Qlik in the Leaders Quadrant which was "driven by a robust product, an above-average customer experience and a strong global partner network." Breadth of product capability has always been a strength of Qlik and continues to be according to Gartner. As has, user enablement. Qlik's modern BI architecture makes it simple for business users to develop their own BI applications in a governed, data discovery process, without requiring assistance from IT developers, usually needed with other platforms. According to Gartner, "Qlik's ease of use for consumers and its visually appealing dashboards have proven to be product differentiators."

While in the recent BARC BI survey (the world's largest independent survey of BI users), Qlik rated #1 in customer satisfaction and customer experience, so Gartner's Magic Quadrant should also be considered in light of BARC's results.

Smart data discovery

Qlik pioneered Data Discovery BI. Qlik's associative engine (QIX) is the driving force behind Qlik applications. Not only does Qlik support integration with best-in-class natural language processing capabilities, advanced predictive analytics and enables an immersive experience including virtual reality integration through Qlik's open APIs, but the native capabilities of the associative engine and open architecture are the unique foundation for capabilities not easily replicated. The QIX engine works as people think, it intuitively seeks to understand all the possible associations that exist in user's data, across all their data sources and allows them to freely explore that data, asking questions in any direction without restrictions or boundaries. That means no predefining data hierarchies or building data cubes. In short it facilitates what many investments in neural networks are striving to achieve. It enables a unique search experience, associative data prep and profiling, data enrichments, suggestions, labeling, compression, truly smart and adaptive visualisation, and indexing across big data sources. In short it defines 'smart' from data preparation, to finding patterns in data, to sharing and operationalising findings.

Rapid (and scalable) deployment

Some are scared off by the prospect of using BI applications because of the supposedly painstaking transition process and cost involved. Gartner noted that with Qlik, this is not a problem. Qlik has proven to be easy to deploy - and moreover, easy to scale, so you can adjust your use as your business grows in size or scope.

Qlik's scalable, in-memory engine allows lines of business as well as central IT to rapidly mash data from multiple data sources that is then accessible via highly interactive dashboards. While Qlik continues to invest in developing a cloud version of the product for the enterprise, SMB versions are already available.

So what about software cost?

When you look at the Magic Quadrant it always highlights strengths and then weaknesses for each vendor. Interestingly, Gartner indicated that Qlik's cost of software as a potential barrier. It's important to look at Total Cost of Ownership (TCO) though, not just licensing. Qlik has one of the best TCO's in the business, according to Gartner in its BI Platform Ownership Cost research. While BARC's BI Survey in October 2016 rated Qlik #1 also in Project Success and Business Value among large international BI vendors (this was a survey of nearly 3,000 end-users). Almost 70% of a BI project's TCO is not found in the license costs but in deployment, infrastructure and support. For the other Leaders in the Quadrant there are several independencies, implementation costs or you simply need to buy additional tools to get the same features.

Supported by a strong Qlik partner

Whether a Qlik client feels supported or not has a lot to do with the relationship and abilities of the Partner they choose to work with. So don't underestimate this. Inside Info as I mentioned launched QlikView in Australia in 2003 as the Master Reseller and then has continued as the longest standing top level Elite Qlik Partner, having won Partner of the Year for many years as well. With over 100 Qlik reference sites, we measure our success through the quality of our people, the relationships they create and the impact we have on our client's business.

To read more about Gartner’s report, download a complimentary version of Gartner's 2017 Business Intelligence and Analytics Platforms Magic Quadrant below.

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