BI | 7 Valuable Tips for Power BI

Power BI is Microsoft’s interactive data visualisation and analytics tool for business intelligence (BI). Power BI is used to pull data from a wide range of systems within the cloud to create dashboards that track the metrics you care about the most, or drill in and (literally) ask questions about your data. Power BI also allows you to create rich reports or embed dashboards and reports into reporting portals you already use! How good is that! The dashboards, reports and visualisations you can create go far beyond bar and pie charts, but what’s even better is that you don’t need to be a designer to use them. Here at Advance Business Consulting we have shared 7 valuable tips that will help you gain greater insights from the information you already have, in more areas than you might expect.

Let's get into it.

1. Visualise the services you use

Power BI is easily accessible with Microsoft, but what you may not know is that it has hundreds of content packs, templates, and integrations for hundreds of data services and apps—and not just Microsoft ones like Dynamics 365 and SQL Server.

Connect your apps to data

Data is at the core of every app. We make it easy to get your data into your apps with over 200 connectors for many popular cloud services and even your on-premises data.

For example, if your business uses Xero for accounting, K2 Cloud to build business processes, Adobe Marketing Cloud, SAP HANA, Salesforce, MailChimp, Marketo, Google Analytics, or even GitHub, Power BI can be used to visualise the data in those services, create reports against them, and bring them together in a custom dashboard—a CEO's dream!

What's also great is the ability to set up the on-premises gateway to use Power BI to explore data sets on your servers. That way you can compare website visitors with sales, or see which promotions have brought in new customers. You can create your reports and visualisations, perform calculations (Power BI calls these calculated measures) and set access levels for individual users, data sources, or specific dashboards and reports to control who can view more sensitive information.

2. Tell stories with your data

We all know charts are great for numbers, but if you want to show information that changes over time in a way that’s easier to understand, try the new Timeline Storyteller custom visual for Power BI. This allows you to create a linear list of dates or times or lay them out in circles, spirals, grids or custom shapes. You can also show a chronological list, a sequence that shows the duration of events, or pick relative or logarithmic scales. Pick how to best represent, scale and lay out your data and Power BI will build a timeline from it; use that to tell the history of your business, show how demand is growing, or explain anything else in which the sequence of events matters.

3. Explore ‘What-ifs’

You can spend time comparing different scenarios in Excel, but Power BI lets you do it by dragging a slider bar to show changes. Add a calculated measure for a figure such as revenue and you can use the New Parameter button in Power BI Desktop to add parameters that change in your What-if scenario – setting the data type, minimum, maximum and increments. That creates a calculated measure that you can reference in other calculated measures; so if you create a What-if parameter for the number of customers who respond to a particular promotion you can plug that into a formula that you create to show how many customer support tickets you can expect to have to deal with. Tick “Add slider to this page” in the What-if parameter dialogue to add a slider bar that you can drag to show the difference when the number of customer responses is higher or lower. Forecasting has never been easier!

4. Ask questions in real time

Instead of designing charts and reports, use the natural language features of Power BI to ask questions and get visualisations in response. You can specify the way the data is presented — ask for “total sales by region by month as a line” — or let Power BI pick a layout that suits the data with a more general question like “What were the sales numbers for last quarter?”.

If there are tiles pinned to the dashboard, Q&A will suggest those as questions, and as you type a question it will suggest terms you could add based on the tables in the data set. If the question turns out to be extremely useful, you can pin the visualisation to the dashboard, making this an easy way to create visualisations for a data set. If you own the data set, you can also add featured questions in the dashboard settings. Q&A uses the names of tables, columns and calculated fields in the data sets; if the column is called area rather than region, you’d need to ask for “sales by area” unless you add synonyms, and table names like CustomerSummary will make Q&A less natural than names like Customers (even though Q&A would know that’s the table you want if you ask about “customer summaries in Chicago” because it can break words up and understand plurals).

Power BI Q&A works on the Power BI website and the iOS Power BI app. It can work on data stored in an Excel table (or in a database via the on-premises gateway if you enable Q&A for the data set) or you can use Power Pivot to optimise the data set for Q&A. Make sure all the tables in your data set are joined correctly, check data types for dates and numbers, and create the default field set for columns and default label for tables to tweak the columns displayed and the type of graph or chart Q&A will show.

5. Implement custom visualisations

Power BI includes a good range of visualisations, and you can add more, either by downloading them from the Microsoft Store or by creating your own with the open-source Power BI Custom Visual Tool (which uses CSS, TypeScript and NodeJS). Don't stress, our team is experienced in implementing custom reporting for you. 

The Office Store includes visualisations from Microsoft, like word clouds, a correlation plot based on R script, chord charts to show interrelationships in a circular matrix, the “box and whisker plot” that highlights outliers, clusters and percentiles to show data that might otherwise get lost in summarised figures like averages, as well as visualisations created by other Power BI customers.

You can also link Visio diagrams to Power BI to use those as custom visuals, if you want to analyse progress through workflows and processes. If you have Excel analytics models, you can use Frontline’s Analytic Solver to turn them into custom Power BI visualizations without having to design the custom visual in JavaScript. What you get isn’t a static report; it’s a dynamic model that you can drag and drop different Power BI data sets onto to simulate or optimise different options.

6. Fit more data into executive dashboards

It isn't uncommon for different BI users to need different levels of information in their visualisations. Managers and business analysts may want a lot of details, but if your executives are tracking 20 or 30 key metrics, maybe for multiple regions around the world, it’s better to present that at a glance with a simple view that shows the target and the actual figure rather than a more complex visualisation. That way you can look up information quickly in a meeting without getting lost in too many charts and figures. We all know how frustrating that can be! The Power KPI custom visualisation combines multiple report types into a single tile.

7. Power BI works with IT data, too

It isn’t only business users who have large amounts of information they need to shave down for insights; you can use Power BI to visualise data for IT monitoring tools. The Power BI solution template for Azure Activity Logs uses an Azure SQL database and Stream Analytics to collect logs and display them using pre-built Power BI Desktop reports, so you can look at trends in usage and problems. There’s also a set of pre-built Power BI reports for the Intune Data Warehouse that shows device details like configurations and compliance state, and a solution template for System Center Configuration Manager with a dashboard that covers client and server health, malware protection levels, software inventory and which devices are missing updates.

Power BI's flexibility also gives users a chance to build their own dashboards and reports for other tools, as long as they can get the data into an SQL Server or Azure SQL database. This is a game-changer!

Advance Business Consulting is experienced in Power BI implementation, to learn more about how it can assist your business, contact us today!

Whitepaper | Unlocking the value of workplace automation.

Discover how AI can streamline your search process and provide the information you need, when needed.

Knowledge work automation is dedicated to streamlining a professional’s tasks to eliminate anything that does not make the best use of their skills. This technology-driven, interdisciplinary approach focuses on bringing together all the tools a professional needs to minimise the time they spend on flow-breaking tasks that should not require their dedicated attention. Enter your email to access this useful guide.

Download the whitepaper:

To discuss how you automate work and be more efficient contact us, and an expert will get in touch with you.

Email: sales@advance.net.au

Or call us on +61 8 8238 6500

Machine Learning with Unstructured Content: Text Analytics

What is Text Analytics?

Often when we think of machine learning, we think of models that predict an outcome... we don't often think of how these models can be used to predict the sentiment and themes of text data. Text Analysis leverages machine learning and natural language processing capabilities to help businesses extract insight from text data. By converting raw text or unstructured data to structured content using machine learning algorithms, allows business users to understand the key constructs in their underlying text. Below are some of the key functions that text analytics performs: 

1. Text Preprocessing: Cleaning and formatting the text data to prepare it for analysis. This may include removing stop words, punctuation, and stemming words to their root forms.

2. Sentiment Analysis: Determining the emotional tone and polarity of the text (e.g., positive, negative, neutral) to gauge customer sentiment. Good Text Analytics tools will also provide a numeric sentiment score so that users can ascertain the extent of the polarity (i.e., very positive or very negative). 

3. Entity Recognition: Identifying and categorising entities such as names, locations, and products mentioned in the text. Text Analytics can extract entities such as brands, countries, products, etc. 

4. Topic Modeling: Discovering prevalent themes and topics within the text data. This is a critical component of Text Analytics, as it allows businesses to identify key themes, as well as define rules for the classification of words and/or phrases (sometimes referred to as "Queries"). 

Note: Text Analytics is not a word cloud. Word clouds are a very simple representation of commonly mentioned words in a given text data set, but does not provide the richer capabilities mentioned above. There are better ways to analyse and visualise outputs from Text Analytics; please get in touch with our team if you want to learn more about these. 

Why Analyse Text Data?

Text analysis plays a pivotal role in three key areas for businesses: Customer Insights and Feedback Analysis, Competitive Intelligence, and Operational Efficiency and Risk Management. Firstly, it enables organisations to gain valuable insights from customer reviews, feedback, social media mentions, and customer experience interactions. These can help with facilitating informed decisions to enhance product development, marketing strategies, and customer experience. 

Secondly, text analysis aids in monitoring competitors by analysing public sources, allowing businesses to identify market gaps and refine their strategies. Understanding what your target customer perceives about your competitors and/or their products is incredibly valuable, especially if this data can be obtained from mechanisms that carry less bias (such as review sites for example). 

Lastly, it can improve internal operations by analysing employee feedback and communication, while also serving as a tool for proactive external risk management by monitoring news articles and social media for emerging threats.

These applications collectively empower businesses to make data-driven decisions and improve overall performance, using unstructured text data that would have otherwise been cumbersome or impossible to analyse.

Text Analysis for Customer Insights and Feedback Analysis

Understanding customer sentiment and preferences is paramount for any business. Text analysis allows organisations to delve deep into customer reviews, feedback forms, social media mentions, and customer support interactions. By analysing this unstructured text data, businesses can gain valuable insights into what their customers like, and dislike, and what problems they face. This information can inform product development, marketing strategies, and customer experience improvements, ultimately leading to higher customer satisfaction and loyalty (and spend) while reducing churn.

Example: A call centre is an important component in enhancing customer experience and decreasing customer churn. Conventional models for predicting customer churn primarily rely on customer data gathered from past transactions and demographic information. However, this approach overlooks the inclusion of important context provided directly from customers, including their needs, desires, wishes, and emotions. Text Analytics is capable of generating categories like billing problems and product issues, which can then be incorporated into predictive models. This valuable information provides insights into the purpose behind each customer interaction and customers' motivations, resulting in a 2 times faster reduction in customer churns on average. (Source: Lexalytics)

Competitive Intelligence with Text Mining and Text Analytics

Staying ahead of the competition is a constant challenge in today's fast-paced business environment, particularly as businesses fight for share of a decreasing wallet. Text analysis can help businesses monitor their competitors' activities by analysing public sources like competitor reviews, news articles, and social media discussions. By tracking and analysing competitor sentiment and customer feedback, organisations can identify gaps in the market, capitalise on their competitors' weaknesses, and refine their own strategies to gain a competitive advantage.

Driving Operational Efficiency and Risk Management with Text Analysis Techniques

Text analysis can be applied internally to improve operational efficiency and risk management. By analysing employee feedback, internal communications, and performance reviews, businesses can identify issues within the organisation, such as low morale, communication breakdowns, or operational bottlenecks. This insight can be used to streamline processes, enhance employee satisfaction, and reduce operational risks.

Additionally, text analysis can also be used for monitoring external risks. By analysing news articles, social media, and industry reports, businesses can stay vigilant to emerging threats, such as public relations crises or market disruptions, allowing them to take proactive measures to mitigate these risks.

Example:  As a food and beverage research company, Technomic’s data analysts had the challenge for categorising ingredients provided by a data vendor. Using a trained machine learning model, they were able to automatically put ingredients in the appropriate sub-categories at over 98% accuracy, saving Technomic up to 40 people-hours of labour per category. (source: Lexalytics)

Incorporating Text Analysis Outputs into Machine Learning Models

Text analysis can be a valuable component in building predictive models, especially when dealing with unstructured text data. For example, when predicting a customer's propensity to repurchase, a business could utilise unstructured feedback from multiple channels (email, call centre, and surveys) to identify key themes and sentiment indicators that can be incorporated into a predictive model. Here are some other areas where Text Analysis can be incorporated into Machine Learning models:

1. Feature Engineering: Text analysis helps convert unstructured text into structured features that can be used in predictive models. This involves techniques like sentiment analysis, entity recognition, and topic modelling. These extracted features can be combined with other structured data to improve the predictive power of models.

2. Sentiment Analysis for Customer Churn Prediction: Suppose a telecom company wants to predict customer churn. By analysing customer comments and reviews, sentiment analysis can be applied to gauge customer sentiment towards the company. Positive or negative sentiment scores can be used as features in predictive models to forecast the likelihood of a customer leaving the service.

3. Text Classification for Spam Detection: In email or message filtering systems, text classification can be employed to distinguish between spam and legitimate messages. By analysing the content of emails and messages, the model can predict whether an incoming message is likely to be spam or not, enabling automatic filtering.

4. Topic Modeling for Content Recommendation: Streaming platforms like Netflix use topic modelling to recommend content to users. By analysing the text descriptions, reviews, and user feedback for movies and TV shows, they can create predictive models that suggest content based on a user's viewing history and preferences.

5. Customer Support Ticket Resolution Time Prediction: Customer support teams can use text analysis on support tickets and queries. By examining the text for keywords, sentiments, and complexity, predictive models can estimate the time required, as well as the best team to resolve a customer issue, enabling better resource allocation and improved service levels.

6. Market Sentiment Analysis for Stock Price Prediction: Financial institutions can use text analysis to analyse news articles, social media posts, and press releases related to publicly traded companies. Sentiment scores extracted from the text can be integrated into predictive models to forecast stock price movements.

7. Review Ratings for Product Sales Prediction: E-commerce platforms can utilise sentiment analysis on product reviews to predict future sales trends. If a product consistently receives positive reviews, the predictive model can forecast higher sales for that product in the coming months.

   Bringing it all Together

   It is important to create and understand the relationships between the insights extracted from Text Analysis. For example, it is not enough for a retailer to understand that their customers are talking negatively (sentiment) about shoes (topic). The retailer would also need to understand other themes that are related to or occurring at the same time as these, such as sizing or availability, in order to provide richer context. Similarly, when analysing competitor reviews online it would be more useful to understand all the relevant context together. This may also require the integration of other operational data that could impact decision-making related to the Text Analysis.

   Getting Started

   Text Analytics is an exciting application of machine learning and NLP, that is also mature from a technology perspective. Even more exciting is combining the results with other traditional machine learning models and predictive analytics. While the technology exists, it is important to ensure that it is implemented appropriately.

   Leverage our team's experience with machine learning and text analytics; get in touch with us to book a free consultation to understand the opportunities you have to implement unstructured text analytics and drive better decision-making in your business. 

5 Real World Examples Using Predictive Analytics to Reduce Customer Churn

It's a well-known marketing adage that it's more expensive to acquire new customers compared to retaining existing customers. However, customers have become more discerning and have many mechanisms to shop around for alternatives. At the same time, there has never been a more important time in business to reduce costs and improve the return on sales & marketing efforts. One way to do so is to reduce customer churn. The challenge is that it's not always apparent which levers will be best to reduce churn, as well as how those levers can be integrated into everyday business processes in an automated manner. This is where Predictive Analytics can play a crucial role, firstly by identifying the levers and secondly by mitigating the risk of human bias in our decision-making. The good news is that while machine learning and predictive analytics used to be the realm of data scientists and engineers, modern tools are providing the means for business to test and implement these models into their processes. 

Below, we have summarised 5 key considerations for using Predictive Analytics to reduce customer churn. The proof is always in the pudding though - if you would like to book a free Machine Learning workshop with us, contact us today. 

1. Use Predictive Analytics to Understand Customer Behavior

Predictive analytics can be applied to customer data to gain insights into their behaviour and preferences. By analysing historical data, businesses can identify patterns and trends in customer behaviour that are markers for a desired customer outcome (e.g. repurchasing). This analysis can help businesses understand why customers churn and what factors contribute to their behaviour. With this understanding, businesses can take proactive measures to address those issues and prevent customer churn.

Example: Harley Davidson harnesses the power of predictive analytics to identify potential buyers, attract leads, and successfully seal the deal. Harley Davidson relies on their AI program to identify individuals who have the highest propensity to make a high-value purchase.   From there, a sales representative takes charge, reaching out to these potential buyers and guiding them through the purchasing journey until they find their dream motorcycle. By directly targeting customers, they can ensure a highly customised experience which ultimately results in greater satisfaction. Predictive analytics helps provide a personalised service to customers when they're ready to buy, while allowing the business to concentrate their efforts on serious buyers. (Source: Forbes)

2. Leverage Predictive Analytics to Identify Churn Indicators

Predictive analytics can also be used to identify churn indicators. By analyzing various data points such as customer demographics, purchase history, and engagement metrics, businesses can build predictive models that can identify customers who are at a higher risk of churning. These models can help businesses take targeted actions to retain those customers, such as offering personalized discounts or reaching out with proactive customer support.

1. Focus on attributes that the business can change: It is important to identify and analyze factors that the business can actually control and influence. This will allow for effective interventions to be implemented in order to reduce customer churn. 
2. Choose only a handful of indicators to focus on: Instead of analyzing a large number of attributes, it is recommended to identify a few key indicators that have the highest impact on customer churn. This will help in simplifying the model and making it easier to interpret and act upon. It is crucial to prioritize the attributes that are most relevant and influential in determining customer churn.
3. Experiment with results so that you can measure impact: After identifying the key attributes, it is essential to conduct experiments and tests to measure the impact of each attribute on customer churn. This can involve running A/B tests or implementing targeted interventions to gauge the effectiveness of changes made to these attributes. By continuously experimenting, businesses can refine their predictive models and improve their ability to accurately predict and prevent customer churn.

Example: Hydrant, a Wellness brand based in the US,  has successfully leveraged Predictive Analytics to identify churn indicators and predict churn propensity with 83% accuracy, while increasing conversion rates and average customer spend by 2.7x and 3.1x respectively, when compared to control groups. The predictive model creates detailed forecasts for each customer's possibility of churn. With these accurate individual forecasts, Hydrant dynamically segments customers to receive tailored marketing messages and discounts that match their future buying power. (Source: Pecan.ai)

3. Use Predictive Analytics to Personalize Customer Experiences

Customer Experience is where the brand promise is delivered, and where expectations are either met, exceeded, or missed. Often, the challenge is understanding where the customer is in their customer journey and what initiatives would nudge them to a business goal based on their own individual context. Integrating predictive analytics models into the Customer Experience enables businesses to tailor their interactions and offerings to customers as a segment. By understanding customer preferences and behaviour, businesses can provide personalized recommendations and offers that are more likely to resonate with customers. This personalized approach can enhance the customer experience and increase customer loyalty, reducing the likelihood of churn.

Predictive analytics can be used to personalize customer experiences by analyzing customer data and making predictions about each individual customer's preferences, behaviors, and needs. Here are some steps to use predictive analytics for personalization:

1. Collect and integrate customer data: Gather data from various sources such as customer profiles, purchase history, website interactions, social media activities, and customer feedback. Ensure that the data is accurate, up-to-date, and properly integrated.

2. Clean and preprocess the data: Cleanse the data to fix any errors, remove duplicates, and handle missing values. Preprocess the data to transform it into a suitable format for analysis.

3. Define customer segments: Use clustering techniques or customer segmentation algorithms to group customers into different segments based on their similar characteristics, preferences, and behaviors. This helps in understanding different types of customers and tailoring experiences accordingly. Pro-tip: Leverage Text Analysis to identify key themes in unstructured customer feedback in order to build richer customer segments. 

4. Analyze and model customer behavior: Use predictive modeling techniques like regression, classification, or recommendation algorithms to understand customer behavior patterns. This can help predict future actions, preferences, and likelihood of certain events, such as purchases or churn.

5. Develop personalized recommendations: Based on the predictive models, make personalized recommendations to customers. For example, suggest relevant products, promotions, or content based on their past behaviors or similar users' actions. This can be done through targeted advertising, on-site recommendations, or personalized emails.

6. Real-time personalization: Implement systems that use real-time analytics to personalize the customer experience in the moment. For example, show personalized product recommendations as soon as a customer visits a website, or tailor the website content based on the customer's browsing behaviour.

7. Measure and optimize: Continuously monitor customer engagement, conversion rates, and customer satisfaction to assess the effectiveness of personalized experiences. Use A/B testing to compare different personalization strategies and fine-tune the models and recommendations based on the results.

Example: Having a truck breakdown is not only a bad experience for the driver and business operations, it also costs the business money.  Using connected devices and machine learning models, Volvo is able to predict when a truck is likely to breakdown, before the event has occurred.  The essence of connected services and proactive maintenance lies in the fact that, thanks to wireless technology and sensors, Volvo can gather copious amounts of real-time data from a vehicle. By analysing this data and identifying patterns, they can effectively forecast and preempt any potential malfunctions. This allows customer to plan a workshop visit at their convenience, and promptly address the issue before it results in an unforeseen breakdown. (Source: Volvo Trucks)

4. Measure the ROI of Predictive Analytics

Measuring the return on investment (ROI) of predictive analytics is crucial to assess its effectiveness and justify its implementation. Businesses can track key metrics such as customer retention rates, revenue generated from retained customers, and cost savings from reducing churn.

By comparing these metrics with the costs associated with implementing predictive analytics, businesses can determine the ROI and make informed decisions about the use of predictive analytics for customer churn reduction. Using A/B testing is a critical component of measuring the success of Predictive Analytics programs, and can be especially effective if tangible metrics such as churn rates and revenue are attributed in the model.

What are predictive models?

Predictive models are algorithms that use predictive analytics to forecast future outcomes based on historical data. These models use statistical techniques, such as regression analysis and time series models, to identify patterns and relationships within the data. By analyzing factors that have influenced customer churn in the past, predictive models can predict future churn and help businesses take proactive actions to retain their customers.

Reducing customer churn is a crucial objective for businesses. Machine learning and predictive analytics can play a significant role in achieving this objective. By using predictive analytics to understand customer behavior, identify churn indicators, personalize customer experiences, engage in proactive customer retention measures, and measure the ROI, businesses can effectively reduce customer churn and improve their overall profitability and growth.

At Advance Business Consulting, we're passionate about helping our customers get the best value out of their data and technology. Predictive Analytics and machine modelling are some of the techniques that our data geeks love to work with our customers on. If you're interested in exploring how these can enhance your business, book a free workshop. 

Customer Story | Accurate data delivers 1834 Hotels a competitive edge with Qlik

In 2021 we held our Innovators 2021 event focussed on client stories about how they tackled COVID-19 and what role technology played during this unique time. You can read the recap and watch the full video of the event here.

Continuing on from the event, we sat down with 1834’s CEO Andrew Bullock to write up this customer story. This case study outlines what 1834 Hotels do, the challenges in managing data and how a business intelligence tool can streamline reporting to free up staff and automate daily business tasks.

Click on the case study below

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1834 Hotels Case Study

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To discuss how to capture, manage and understand your data, leave your details below and an expert will get in touch with you.

Or call us on +618 8238 6500

Cyber Alert | Kaseya Ransomware Attack

Kaseya Ransomware Attack

We are aware of a widespread cyber incident affecting the Kaseya product set. Firstly we want to assure you that we do not employ this product set, and as such you are not at risk through the services that we provide you.

If you do employ Kaseya VSA in other parts of your business, please immediately shut down the Kaseya infrastructure and consult with your cybersecurity provider and the ACSC.

If you would our advice, guidance or additional assistance please contact us immediately.

What is Kaseya VSA?

Kaseya Virtual Systems Administrator (VSA) is a remote monitoring and management toolset designed for use by Managed Service Providers in servicing their customers. It is delivered as both a SaaS product and an on-premise installation.

What is this incident?

Starting from July 2nd, organisations with Kaseya on-premise installations began reporting abnormal behaviour and later, instances of ransomware. While the investigations are currently ongoing, it is strongly suspected that one or more Zero-day vulnerabilities in the Kaseya VSA toolset were exploited to deliver the ransomware payload.

These vulnerabilities were first discovered in April by the Dutch Institute for Vulnerability Disclosure (DIVD) who disclosed them to Kaseya, however, a patch had not been released when the ransomware attacks began.

The attackers responsible have demanded $70 Million (USD) to decrypt all impacted devices and advised they will negotiate on an individual basis if approached.

Would I have been protected?

From the direct attack, the simple answer is no. However, there several other defensive layers that, if implemented, would have completely prevented or slowed the ransomware outbreak once it entered the environment.

Due to its nature as a Zero-day, the initial payload would have been extremely hard to prevent, however other layers such as application control software, intelligent behaviour-based protection software and a cyber incident response plan would make a significant difference to the amount of disruption (if any at all) a business would have suffered as a result of having the Kaseya toolset installed.

If you would like to complete a paper-based exercise to see how your cyber defences would have fared against this attack, and proactively identify any areas of improvement, please get in touch with us as soon as possible.

Where can I find out more?

The Australian Cyber-Security Centre (ACSC) alert

Cybersecurity & Infrastructure Security Agency (CISA-FBI) advice

Cyber Alert | 'Missed Call' SMS Messages - Latest Cyber Threats

‘Missed Call’ SMS Messages

We are aware of a recent increase of SMS messages which appear to contain a link to a new voicemail, but in fact are spreading a computer virus to mobile phones.

If you have received one of these messages but have not clicked the link then you have no need to be concerned, you are safe.

If, however, you have clicked the link and installed the app, it is highly likely you are infected with a virus called Flubot.

How can I tell if I’m ‘infected’?

• You may have received a SMS message from an unknown number advising you that you have a missed call or voice message, with a link to access it.

• You may have a new app called “Voicemail”

• You may receive phone calls or SMS messages from other people advising that you have sent them messages that you are not aware of

• Your mobile phone provider may alert you that you are sending large volumes of SMS messages, or that your device may have been infected by malware

• At present, we are only aware of Android devices being susceptible to this virus, however, this may change to include iPhones in the future

What can I do if I am ‘infected’?

• First, talk to your financial institution. The makers of this virus have already used the information they gained to steal money from several Australian bank accounts. Make your financial institution aware you have been infected, they should guide you through the relevant processes to protect the accounts they have in your name.

• Remove the virus - Many popular anti-virus products for Android will remove this virus, alternatively a factory reset can be used to remove the virus.

• However, when restoring your phone be careful, as the virus will be saved in the backups as well. If a backup is needed use one from before you received the first SMS message.

• Next, consider other information the virus may have gotten access to. Once infected, the virus will have likely gained access to all your files, notes, messages, saved passwords, email history and all other data stored on your phone.

• Consider the implications of each, and any passwords that might now need to be changed. Your email account password is a very important one, as your email can usually be used to change most other passwords

• If in doubt, consult a professional to help you with the process.

BI | Why you need a plan to implement business intelligence.

You want to get the most value out of any new business system implementation. Whether its new insights, automating management reports, a new operational dashboard or some predictive analytics to help make better decisions.

From our experience, a roadmap and some planning before you start development will help avoid the common issues that can cripple a business intelligence project. Resolving a disconnect with a major stakeholder halfway into a project is a challenging situation and it can be financially costly and bad for customer satisfaction.

At Advance, we’ve been working on implementing business systems for over 20 years and have seen it all. We’ve picked up the pieces of some very poorly implemented projects. Many of the challenges are common to all projects and some simple planning in the beginning will provide the best opportunity for a successful outcome.

• Avoid the common traps and follow these steps. Spending some time on good planning early on will pay off in the long term.

1 - Get the main stakeholders in the same room.

Set up a short 1-hour meeting, outline the benefits and examples of successful BI projects. Get people excited about the project and what it will deliver. BI can free employees from manual, inefficient and low-value work. Managers can keep their team accountable and gain new insights on performance. Business owners can see key performance indicators instantly, even on their mobile devices. Mobile BI with instant messaging can provide an avenue for instant feedback so you can begin corrective actions.

• Getting the key stakeholders onboard early is a major success factor to any project.

2 - Agree on the key problems you want to solve

There will be several problems you want to solve. Agree with the stakeholders on the 5 most important problems they want to resolve.

Write them down, define how the ideal solution looks, is it measurable, achievable, timely. It needs to be measurable!

Based on the discussion, prioritise. Depending on the feedback you might pursue a quick win, like automating a daily report or look at something bigger like a new dashboard linking a number of key business systems. BI will provide an opportunity to connect data from different sources like Excel, SAP, MYOB, Xero and Salesforce for example. This means you can get a holistic view of the business and connect data, something that was not possible with data silos.

3 - Agree on how success is measured with Key Performance Indicators (KPIs) 

Think of KPIs as the mechanism to make effective, data-driven decisions. You are far more likely to improve what you can measure. This is what underpins a successful data driven business

Agreeing on the right KPIs will help in driving the efforts of the company towards a meaningful outcome. To rally the team, you need to measure the right things.

• Don’t share too many KPIs, as a data analyst you will lose your audience and overwhelm the typical employee.

KPIs vary from each department. Agree on something achievable like 10 KPIs max.  Below is a list of common finance KPIs relevant to most businesses:

 •   Working capital

•    Operating cash flow

•    Return on equity

•    Quick ratio

•    Debt to equity ratio

•    Inventory turnover

•    Accounts receivable turnover

•    Gross profit margin 

4 - Data

Getting access to the data is one of the first steps to building a BI solution. Map out the various systems used and get the ball rolling early on whether you have direct access or what data APIs will provide. 

• Access to the data can hold up any project. Dive in early to assess what you can get.  

We say do this early as some systems will provide different levels of access and data quality. More mature enterprise systems like SAP will more likely provide access to everything you need while other less mature vendors often need far more manipulation to get what you need. Perfect data is unlikely and getting access as soon as possible will help reduce delays caused by waiting on 3rd party vendors.  

A good data management framework will help to get the best possible data, the best data you can get will directly impact on insights. Test the answers and iron out any inconsistencies before rolling out the solution to a large audience.

• Trust is hard to win back if the new system is not showing accurate information. Don't let this happen, if there is an issue, acknowledge it and resolve it.

5 - Action

Deploying a new system should drive new insights, new actions and opportunities. Use the new insights to make a positive step forward. Set up a system to action the data and new insights. First - Automate the delivery of reports, and have a clear strategy on what employees should do with this information. For sales teams, a weekly dashboard of KPIs will drive behaviours and actions. Make the most of this opportunity to get the team excited about new insights. Ensure the time to action KPIs is managed with clear deadlines.

Final Thoughts

• Even if you achieve only a couple of the steps above, you will increase the likelihood of deploying a successful business intelligence solution.

We haven’t touched much on the software for BI and this really comes last. Each tool has its strengths and we tend to lean towards Power BI and Qlik just to be transparent. Most modern BI tools can get the desired outcome and some planning early in the cycle will make a big impact.

Like to know more? Contact us here or check out our blog on two leading BI solutions - Power BI and Qlik - Some interesting changes at Qlik and what to look for in a business intelligence solution.

BI | Drowning in Excel reports. Employee retention. Some unexpected benefits from deploying a business intelligence platform like Power BI and Qlik.

Here is one recent example of how a business intelligence tool can deliver more than just new operational insights.

• The client: Multiple systems, multiple sites, time and labour-intensive manual reporting

• The result: Timely, automated reports, new insights with an instant feedback portal

• Next Steps: Deployed to mobile with chat, user accountability and predictive analytics

Managing a business is very much about the people that you work with. The clients that rely on our services to run their business and the employees at Advance that are responsible for delivering these business systems. Clients and employees both need to have a good level of customer satisfaction or relationships can fall apart.

It was interesting to hear from my peers about situations where talented employees have left their jobs because of frustrations caused by data overload and using a process that is inefficient, manual, slow and often frustrating. There are times when work will be challenging and that is a part of life, but throwing more labour into a manual process to get the result is not a good long-term solution.

Companies that foster employee growth through technology innovation will improve staff retention. We try to adopt innovative tools early that are good value and this means our team is always learning new skills. The users of these solutions on the client side are eager to adopt a new system if it makes their work life easier and more productive.

Employee satisfaction and retention was an unexpected benefit from deploying a successful business intelligence platform.

Below is a BI solution we have been working on which is quite a common example where daily reporting is needed and there simply aren’t enough hours in a day to manually pull all of the data from the various branches and the 30+ systems. This type of reporting will cause frustration to any employee, especially if they are tasked with manually accessing each branch early every morning to build a complete view of the businesses performance.

The Challenge

• Multiple sites, often in the double digits. 30 sites are not uncommon

• Multiple disparate business systems across different locations, systems like Xero, MYOB, SAP, many others for HR functions and client facing systems

• Be aware that although powerful, API’s are not built equally and something that performs well in a mature system like SAP may not provide the same data and consistency in something like MYOB. The ability to manipulate the data is a critical aspect of connecting multiple data sources

• Time-consuming and labour-intensive manual reporting

• The window for generating daily reporting not big enough to generate reports on time

• Sites spread across multiple geographies and time zones

• Manual, static Microsoft Excel reports to consolidate data into PowerPoint and then emailed each day

versus

Using Traditional Reporting Encountered Some Of These Challenges

• Hardly scalable and very prone to human error

• Time-consuming, manual and inefficient

• Not a lot of fun. Repetitive tasks

• Staff turnover is high

• Inefficient with no automation

• Slow

• Missed opportunities

• No forward projection or predictive analytics

• Linking performance to industry systems that benchmark against competitors in the same industry was not possible

• Reporting can look inconsistent and not well branded when required for management reporting

A Better Solution

• A business intelligence solution connecting all of the systems and data into a single verified view of the truth

• Automated, consistent, branded and uniformly formatted reports and dashboards

• Dynamic insights that can be queried, drilled down for further detail

• Automatic red flag warnings for KPI’s that are underperforming or outliers

• Opportunities for further growth in positive KPI’s

• Data pulled directly from each system, automatically calculated, verified and disturbed in minutes

• Manageable distribution via internal systems like Slack or email to a selected user or group based on title or credentials

• Connected to external data sources such as local weather to provide further insights and predictable analytics

• Easily managed by employees without any special training

• Portal for reporting commentary enabling stakeholder feedbacks

• Secure and only the right people have access

The Results

• Finance now quickly generate required reporting each day for 9:00AM reviews

• Holistic reports for entire business across all 30 locations

• New insights for things like revenue vs payroll

• Automated reports are distributed each day to key stakeholders

• Increased efficiency, productivity and employee satisfaction

• Finance can focus on actions versus generating reports

• Minimal manual reporting – there is always some needed and the human touch.

• Consistent presentation with clear branding

• Instant feedback on the numbers via comments on a secure portal

Final Thoughts

A well thought out BI implementation will connect all these business systems and inputs to build accurate business reports and dashboards. Smarter insights and visualisations with automated reporting will reduce risk and provide the feedback needed to manage a business effectively with a holistic view.

Enabling your team with valuable tools will teach them new skills and a reduction in manual inefficient processes will lead to better job satisfaction.

Tools like Qlik and Power BI are powerful, they will pull together all the systems so you can start building meaningful insights. Qlik is remarkably good at this. By linking to virtually any data source will let you manipulate data to build reports without the need for a data warehouse. The benefit is that it is more cost effective, quick to get answers, often within days not weeks. We have connected to a clients systems in a demonstration right there on the spot and built a report from a live system which is very compelling. Speed to new insights and value is a key benefit when using a tool like Qlik.

A Common Question

How do you get started? The first step to any project is getting access to the data.

If you would like to know more or have any questions about BI, get in touch with us here. We are passionate business intelligence experts.

CONTACT OUR SALES TEAM - NIK VILLIOS | ACCOUNT EXECUTIVE

PHONE: +618 8238 6521

MOBILE: +61 408 800 753

EMAIL: NVILLIOS@ADVANCE.NET.AU

BI | Power BI and Qlik -BI | Some interesting changes at Qlik and what to look for in a business intelligence solution

At Advance, we work with tools like Qlik and Microsoft Power BI when delivering business intelligence solutions to provide actionable insights for our clients. Both tools are market leaders and each vendor has a slightly different approach in delivering new insights. We wanted to take a look at some recent changes in Qlik’s licencing model that enables a more complete BI solution and our view on areas to consider when looking at BI tools.

Want to know more about BI and some outcomes we have delivered? We are passionate BI experts. Get in touch here.

Why would you want a BI solution?

BI offers new actionable insights into your business and will empower employees, deliver automated, efficient reporting and analytical dashboards. BI offers insights to provide new and improved:

• Revenue streams

• Customer experiences

• Business processes

• Competitive insights

• Business performance

• Collaboration

• Unexpected benefits along the way

When looking at a BI solution it is important to take a holistic view of what you are trying to achieve and the key ingredients in the solution. Here are some important considerations:

• Guided analytics and distributed reporting or self-service analytics.

• Is a mobile solution required?

• Existing applications and business systems.

• User skill levels / Experienced developers, business users or both.

• Security.

• Data / Access / Quality / Volume.

• Time to value.

• Maintenance - BI solutions often require ongoing development and support.

• Cost.

Cost needs to be looked at closely, and we mean the total cost of the software, consulting services and training to get a result. It is important to consider ongoing maintenance of the system. It is common for management to ask for further information, new reports, calculations, different formatting and inputs from additional systems.

One BI tool may offer better performance but if it is 10x the cost of its rival and the implementation and support costs are much higher, it will be a difficult business case to justify, unless there is some critical feature like security for regulatory compliance that is a non negotiable requirement. Qlik is very strong in security, backed up by its use in the finance industry by clients like Westpac and ANZ.

Qlik is a market leader in BI, with close to 50 000 customers globally. Let’s take a look at Qlik’s recent announcement about dual-use licencing and a short history of their BI tools.

Dual-use licensing means you can get Qlik’s modern platform – Qlik Sense: Simple, intuitive and visually brilliant and the original – QlikView: Versatile, complex and powerful. This is an interesting offer for existing users and anyone looking at implementing a BI platform.

• Dual-use licencing allows companies to unlock both QlikView and Qlik Sense with a single license key.

• The cost is a 30% uplift in annual Qlik maintenance. (*Qlik press release)

• This is good news for existing Qlik customers offering access to both products at an additional cost.

• Dual-use licensing offers customers a more complete BI offering for both guided and self-service analytics.

Qlik: Our Experience.

We compared many BI platforms when looking at better insights into our own managed services and consulting business as well as offering the service to our clients. Tableau was seriously analysed and considered, and very compelling with a lower cost to get started and great design. After many comparisons, we found Qlik was a better fit for us, more powerful and its ETL (extract transform load) capability was simply better. Tableau is a great tool with some of the best visualisations available. With Qlik, you can pull data from many different sources without the need for a costly data warehouse. Here at Advance, Qlik is one of the main tools we use when developing BI solutions internally and for our clients, Power BI is another key tool with its strengths and a high adoption in the BI arena.

Qlik really is one of the most powerful tools available and difficult to beat when comparing its ability to handle large data volumes and transforming data (matching records, merging sources, preparing for analysis.) QlikView is a genuine enterprise level BI tool.

Our experience with QlikView:

• Ease in connecting to virtually any data source.

• We are technical developers - QlikView is very powerful in its ability to manipulate or transform the data structure by using script statements and expressions in the Qlik load script.

• Speed in building and delivering powerful insights right away. Even in product demonstrations we were able to connect to the data and build dashboards instantly.

• Time to value can be as low as a few days.

• Limited mobile experience with QlikView - We eventually built our own in house application to give us a better mobile experience and additional capability like distributed reporting and Excel integration through KPI Pulse.

A Short History Of QlikView And Qlik Sense. Why Two Products?

QlikView

Qlik Sense

QlikView has been the flagship product from its founding in the early 1990s through to around 2014, when they introduced Qlik Sense. Since the launch, Qlik has arguably spent more of its development resources on Qlik Sense, a mobile responsive and more visually appealing BI tool. With that said, the 30 000+ QlikView user community has ensured Qlik release new versions of QlikView annually. Some speculate the move towards Qlik Sense might be to better compete with modern and visual data exploration platforms like Tableau.

From our experience, QlikView developers like us find it easier to get results straight away using QlikView when compared to Power BI and Qlik Sense. Important insights with drill down capability right away.  QlikView may not look as visually appealing out of the box as Qlik Sense, but more experienced developers can get complex answers quickly, then make them more presentable for public consumption.

Users coming from a programming or data science background are more likely to find QlikView more flexible and powerful. In contrast, for brilliant looking visualisations and self-service analytics - Qlik Sense shines in this area and the mobile experience is responsive meaning that the platform automatically resizes objects. This is important when working across different platforms like mobile phones and tablets, all with different versions of operating systems. Qlik Sense wins here in delivering a modern mobile experience.

Key Differences And Strengths Of Each Product.

Final Thoughts

Qlik offers a leading BI solution and dual-use licensing is a good thing. It highlights that they want to offer more value in this competitive space and they need to. Power BI offers a comparatively low entry cost and provides a very good BI platform. You can read some of the reasons why we have seen a big spike in demand for Power BI here. Is Qlik the right solution for you? It is a powerful tool but definitely not the lowest cost option.

A thorough analysis of the project needs to be undertaken. Experienced BI experts can provide advice on which tool is a good fit based on outcome required with budgets and total cost in mind. This will help you make an informed decision on the right platform for your business.

Qlik’s new licencing offering is an interesting proposition for anyone looking at a implementing a BI platform. Current users of QlikView can continue developing and supporting existing deployments and try newer features in Qlik Sense for a lower cost than purchasing two seperate tools. This move will also grow interest and additional enquiries for Qlik.

If you are an existing user of Qlik or someone looking to tackle a new BI project, it is a great time to take a serious look at Qlik. There a many great BI platforms out there, Tableau and Power BI are also leading offerings and each has its strengths that really need to be considered and aligned to your business and what you are trying to achieve.

Want To Know More?

You can reach us here or email sales@advance.on.net directly with any queries. BI is our passion and expertise.

We’ve included links to additional content and useful comparison in the Qlik datasheet below.

Additional Insights

Below is a great 5 minute video about Qlik’s April 2019 updates.

Qlik Sense and QlikView Data Sheet PDF

Many Thanks,

John-Paul Della-Putta

Director

Advance Business Consulting

Phone: +61 8 8238 6500

Email: jp@advance.net.au

LinkedIn: www.linkedin.com/in/johnpaul

Website: www.advance.net.au

BI | Spike In Demand For Microsoft Power BI - Here's Why

We review and analyse our enquiries each week to see what our clients are interested in and what challenges the broader market is trying to solve. Business intelligence and new insights is our thing after all.

Unsurprisingly there has been a big spike in the demand for business intelligence solutions, the bulk being for Microsoft Power BI and Qlik.

One of the projects we are working on this week is to provide a detailed financial reporting system from the popular Xero accounting system. Xero is a great tool but our clients are telling us that they cannot easily get the level of detail and analysis they need. The data is there but there is no easy way to get more complex insights. Power BI can help.

If you would like to know more about business intelligence or Microsoft Power BI and what it can do for your business, reach us here

Here are some of the reasons why there is a demand for Microsoft Power BI

• Peer Insights Matter - Microsoft has a 4.3 rating at Gartner Peer Insights with over 1300 reviews today and received the Customers Choice 2018 award from Gartner. This is important not just because Gartner is a leading research and advisory company but also because the very people that use the tool have provided a review. Look for the genuine reviews, it’s one good source for critical honest feedback. Take a look here.

• Australia has a big Microsoft presence and existing clients can access Power BI at a low cost. The desktop version is free for individual users. This makes it pretty attractive to consider using Power BI.

  Wide User Base Appeal - Power BI is targetted at non-data scientists, business analysts as well as power users like developers and data scientists, this means it appeals to a big audience. We work with customers that are power users and self taught BI users, generating their own powerful insights for their business units. The support community is very active and helpful.

• Power BI can easily capture and assemble data and access diverse data sources, particularly other Microsoft tools and platforms.

• Tight integration with Office 365 products, Azure cloud, Dynamics 365, Salesforce, SQL DB, Excel, and SharePoint.

• Analysts have judged Power BI to be a leader. Don’t buy into the hype but also don’t discount genuine endorsements. Current users are also some of the best people to give you an honest review.

• Microsoft has been investing in its Marketing efforts globally and this is creating awareness and demand, this is not a bad thing. Microsoft believe in their product which is backed up by monthly enhancements and updates. Many integration companies and end users agree. There is real investment in this tool.

These are just some of the reasons why people are looking at Power BI. Microsoft is investing heavily in the tool to stay ahead of its competitors and is releasing major updates regularly.

Is Power BI the right tool for you? There are many things to consider and we will discuss this in an upcoming blog. Which BI tool is right for you.

Below is a great overview of the major Power BI updates for March:

Big Data | Make Better Decisions: Don’t Buy Into The Big Data/Small Data Hype

Simulated Gas Leak Fire - Training Centre at Brukunga, South Australia. Photo Taken by Megan Rogerson

Did you know you aren’t supposed to put out an electrical fire with water?

The reason is that the electric current can flow back up with the stream of water and electrocute you.

With a LPG fire you actually want to isolate the gas and not extinguish the flame.

This is because if you extinguish the flame, you can create a much more dangerous environment where you lose sight of the leak and there is also the potential for a deadly explosion.

Despite this, people still get hurt with trying to extinguish common fires for two main reasons:

1. They apply the wrong information to their decision making process (that water puts out all fires)

2. They don’t have all the details (that the fire is electrical or a gas leak in the first place)

Another reason is that they are human and they panic! Dealing with a fire is a stressful situation, if you have ever been in this situation you will know that it is easy to make a bad decision based on what you believe is the right thing to do. Fire progression is rapid and ferocious.

Businesses experience the same issues when using big data.

First, let me define these two terms. Small data is data that is 'small' enough for our consumption and importantly it is actionable, informative and accessible. Big data relates to data sets that are far too large and complex for humans or even traditional software systems to deal with.

Why data science fails

Data science fails most businesses because people tend to ‘cherry pick’ and use data to:

• Confirm bias

• Observe patterns that aren’t there

• Make decisions based on non-cohesive data points

The worst part is they don’t know they are doing it! Just like people who don’t know their fire is an electric one and try to douse it with water, businesses end up hurting their revenue when they make decisions.

So what’s the solution?

Small data is one of the answers, here’s why.

The Cunning Beauty Behind Small Data

To understand the impact small data has, we need to understand the issues with big data and the data science business.

Big data is a popular term and there is lots of hype around it. Every major software vendor has added it to their marketing campaigns and it is also psychologically appealing.

We are trained from an early age to believe there lies a strength to numbers. In fact, from an early age, we are socially branded to think this through phrases like,

‘The more the merrier.’

Our minds are programmed to look for patterns. With big data that can be a problem.

When looking at big sets of information, you get the opportunity to identify lots of patterns.

Not only that. The bigger the data, the greater the chance of being able to draw the connections you want to see, even when they aren’t there.

This practice is so common it has a name: Analytical Bias

To be fair, the data science business tries to combat this. The issue is that by the time the message gets from the data driven business to the regular business, it is either watered down, too late, or forgotten altogether.

Another issue with large data is its momentum.

Big data is slow by its very nature. By the time most companies can finally use it, the content can be dated or no longer viable.

To combat this, you need your data to be accurate and current so you can make business decisions in real time.

Why businesses love the agile nature of small data

Businesses that leverage small data can quickly adopt it into their business and for good reason.

Small data is agile.

With small data, you can assess market need, interest, and viability in real time and decide if you want to profit as an early adopter, or save your investment for a better alternative or opportunity.

Small data is bite sized pieces of information that you can digest and act upon. This is one of the reasons why businesses love small data. Small data is actionable.

Final Thought

Complex large data set analysis is important. Big data is an interesting topic and its potential is compelling, just don’t buy into the hype and don’t pursue it until you’ve done the easy stuff first.

With small data you can have a quicker ROI with some easy wins right away, and valuable insights can be gained with powerful, inexpensive tools and techniques.

Tools like Qlik and Microsoft Power Bi make it quite easy to answer important questions quickly. You don’t have to wait a long time to get the right answers and useful dashboards can be built in just a few hours.

If you’d like to hear more, join our mailing list to get regular updates, articles, ideas, and announcements from the front lines of the data industry.

We work with clients each day to provide valuable insights into their business. This week we are building a new dashboard using Power BI for monthly management reporting.

If you’d like to get in touch or comment on an of my blogs you can reach me directly via my contact details below.

Many Thanks, Jp.

John-Paul Della-Putta

Director

Advance Business Consulting

Phone: +61 8 8238 6500

Email: jp@advance.net.au

LinkedIn: www.linkedin.com/in/johnpaul

Website: www.advance.net.au

Desktop Widgets Help You Focus

Remember when ‘fidget’ desktop toys spun into our lives and dominated the anti-anxiety toy market?

One day people were spinning pens then almost overnight the office was filled with the sound of people clicking buttons and spinning mini-flywheels. It’s always fun to witness the hive mind adopt the newest thing in a line of tools to stay focused.

It’s even more fun when the hive mind just as quickly abandons a trend when the news gets a hold of it. The photo above is from our office, a graveyard of spinners on one of the spare desks. Just like when the news revealed that fidget tools did nothing to help you focus. Just as quick as the toys found their way into the office limelight, they were gone.

Focus is such an important topic in the corporate world. Why do you think caffeine is the only drug that is socially acceptable to brag about overconsumption and dependency. “Don’t talk to me until I have my morning coffee or two!”

Shareholders demand year on year returns and the corporation C-suite has a fiduciary responsibility to max out those returns. CEO bonuses hinge on managers making their teams more productive and profitable. So managers try everything they can to help teams to become and remain focused.

I've seen managers try everything from:

• Mid-Day Yoga Sessions

• Meditation

• Removing Sugary Snacks And Drinks From The Office

• Piping In White Noise Over The Speakers

• Wild Products With No Scientific Evidence (see 10 bunko gadgets here)

Most of it does not work, and the reason ‘why’ you would never expect.

Why Most Tips To Focus Fail

To understand why most ‘focus tips’ don’t work, let’s take a look at how focusing works.

Focus is a state.

However, like other states, it can’t be accessed immediately.

Focus isn’t like joy or panic which respectively dumps dopamine on the brain or triggers the fight or flight mechanism.

No.

Focus is a bell curve that you rise and fall with.

That’s why toys, midday breaks, and similar focus tips don’t work.

Cal Newport explores this in Deep Work. He digs into the topic by explaining that Deep Work (a broad term for focus) results from consistent practice and accessing key signals for focus to take place.

We've kept this in mind when developing a solution to make Qlik metrics more accessible and more powerful. Qlik is one of the main platforms we use when building a Business Intelligence solution for our clients and to measure our success in house. It is one of the leading tools available and we've developed KPI Pulse to extend the reach of Qlik and to provide key metrics easily over email, mobile devices, on desktop widgets or a head up display and directly into Excel.

The broad ideas expressed in Cal’s book reflect a unique KPI Pulse feature that signals focused states with desktop widgets : Here’s How.

Desktop Widget Top Focus Picks

KPI Pulse is a sandbox template design.

Go in and personalise the dashboard however you like.

This addressed a core issue with many Qlik dashboards, busy User Experience (UX)

Busy UX is rarely good.

Our brain has pre-mammalian scripts that help our minds optimise energy, a backup DOS prompt protocol for the human equivalent of safe-mode.

In Thinking Fast And Slow By Daniel Kahneman, the author maps the survival of what he refers to as our ‘lizard mind’. This ‘lizard mind’, Daniel posits, is a survivalist mind programmed to override our state when too many distractions arise.

You see this reflected further in the book Paradox Of Choice.

Their premise at its simplest is this: Too many options causes our brain to give up.

In the early nineties the Chinese government was forced to regulate animated cartoon frame rates, because kids started having seizures while watching TV that reached frequencies of 60 hertz (flashes per second).

That’s why we built-in the custom design element into our solution - KPI Pulse. By simplifying the design, you can optimise UX while cutting distraction and choice paralysis.

3 Focus Tips KPI Pulse Desktop Widgets

TIP 1: CHOOSE YOUR WIDGETS AND STICK WITH THEM

To see a widget means ‘work’. Using the same widget builds your focus on-ramp for your team.

TIP 2: MAKE YOUR WIDGET CHOICE UNIQUE

Only choose a widget that has a unique pull for your industry. Don’t choose something your team might relate to something else. You want the choice you make to be unique to your team.

TIP 3: DON’T GO OVERBOARD WITH WIDGETS

‘If one is good more is better.’ Doesn’t hold true here. Creating too many options will cause choice paralysis.

Final Thought

At Advance and in developing KPI Pulse, we salute our widget technology forefathers, and are committed to pushing forward widget wizardry which has been over 25 years in the making. Small pieces of customised desktop and web content have made their way into our lives whether you call it an accessory, a widget, a web part, or a gadget.

Interested in learning more about how we used psychology, design, and intuitive interfaces to build Qlik dashboards that companies love? Sign up to our mailing list.

Receive valuable tips for data management, Qlik tips, and more.

If you’d like to get in touch or comment on an of my blogs you can reach me directly via my contact details below.

Many Thanks, Jp.

John-Paul Della-Putta

Director

Advance Business Consulting & KPI Pulse

Phone: +61 8 8238 6500

Email: jp@advance.net.au

LinkedIn: www.linkedin.com/in/johnpaul

Website: www.advance.net.au

Did you know colour can alter your thoughts and affect team performance?

That is why colour is the biggest business you’ve never heard of.

Companies dump millions every year into picking the ‘right’ colour for their brand that often results in positive gains.

It’s in your face everyday; Facebook has their iconic blue, Google has their distinctive rainbow palette. McDonalds has their golden yellow arches, the colour code is RGB: (255,199,44) by the way.

Our marketing manager bought a Google Pixel 3 this week and is moving away from his trusty Iphone.

Apple’s approach is to use an aggressive green to deliberately highlight non Apple devices. In contrast they use and a soft, eye friendly blue for iMessages. This is no accident. The new Google Pixel 3 is a pretty innovative device by the way.

Successful companies embrace memorable colours. Colour cultivates emotional engagement and increases productivity by exciting synapse in the frontal lobe. This human trait dates back to our ape origins. Ripe fruit is a more appealing colour than rotting fruit, wouldn’t you say?

In short-colour affects your brain.

That’s why it’s important to pick the right colour scheme for your dashboard.

The be a colour choosing beast, you need to know what colours make your more productive, how to use colour, and how many colours to chose.

To boost your chances for scoring the best colour scheme for your dashboard, we are going to outline 3-key factors to contemplate when mastering your colour selection.

1: The 3-colour tones and how they impact your mind

2: How many colours is too many colours

3: What colours decrease productivity

The 3-Colour Tones And How They Affect Our Minds

There are basic colour tones.

Each colour tone has a specific impact on our mind. To figure out what colours make you more productive, you need to understand what each tone means.

Here are the three tones:

1: Warm - These are reds, oranges, and similar shades.

2: Cool - These are blue, purple, etc.

3: Neutral - These are black, white, tan, brown, and grey.

When choosing a colour tone, optimise the utility of colour by choosing tone that has a clearing and calming effect.

Some colours distract the mind by being linked to other less productive emotions.

That’s why red is great for advertising but bad for educating or focusing.

Neutral colours get the Oscar for best supporting role and are best for accenting main colours. Neutral colours call to mind documents, writing, and similar static elements.

This is why the neutral colours in social media are text.

Cool colours are meditative in nature and are for projecting calm and clarity. Most integrative brands create a seamless experience for customers with blues, purples, and similar shades.

The tone that elicits any response is good, but the right tone will get what you want from your users. Mastering the type is only the beginning, you must now learn to pick the right number of colours.

2: How Many Colours is too Many Colours

Out of the millions of colours, you want to use the ‘less is more’ method.

The rule of thumb for colour branding experts is to use no more than two colours.

One can be just as powerful as two (for all you single people out there).

There is a Goldilocks zone where colours make you more productive, too many colours and it’s distracting too few and people are waiting for the page to load. Simplicity is the ultimate sophistication, draw attention with passionate order rather than disturb a user with a rainbow of chaos.

When adopting two colours, make sure to harness colours that provoke left-brain cerebral prowess. Here’s what to avoid.

3: What colours decrease productivity

To grow happy productive brain activity, it’s wise to be knowledgeable of ADD and depressive colours that are going to be a distraction (Squirrel!).

Here is our list of three ADD and downer colours to consider avoiding for your dashboard.

1: Orange is a bright colour demands attention. Hunters, and construction guys use it all day every day. That’s why sales pages and opt-in buttons are orange. Capture focus, not distract from it.

2: Grey is a bland neutral colour good for highlighting another, like image boarders. Grey induces feelings of sadness and depression especially in women.

3: Yellow is a great colour with a lot of positive emotions attached to it. With that said, yellow often catches the light in an odd way. Even worse, mobile resolutions are different screen to screen. What looks great in the office under your lights will catch the light differently outside.

So what colours make the human mind most productive?

Simple. Calming ones that don’t distract.

Three takeaways:

1. A COLOUR SCHEME IS MEANT TO SIGNAL, NOT DISTRACT. RED IS USED IN ALARMS BECAUSE IT DISTRACTS YOU FROM WHAT YOU ARE DOING.

2. COLOURS ARE FOR YOUR TEAM, NOT BRANDING. KNOW THESE COLOURS ARE THERE TO GUIDE THE USER’S MIND INTO WORKING BLISS.

3. INCREASE PRODUCTIVITY BY MINIMISING CHOICES. WE ALL GET CHOICE FATIGUE. THE MORE YOU HAVE GOING ON, THE MORE DISTRACTING IT WILL BE.

Final Comments:

Let me know your thoughts on colours, there are times existing branding and colour scheme peer pressure designers into selecting a colour scheme. If you are anything like me, you’ve spend hours making sure you are happy with how a report or metric is presented.

Next blog I’ll dive into: Desktop Widgets and how they can improve efficiency

Is Public Wi-Fi Worth The Risk?

Around the world today you can rarely find a café, hotel or airport without access to a public Wi-Fi network. More than ever we have internet access whenever and wherever we need it.

Unfortunately, public Wi-Fi does come with a catch – data sent over a public Wi-Fi connection provides an easy way for individuals with malicious intent to capture the data you send and track everything you do. Using specialised software whilst connected to the same networks allows access to the information you send, like someone eavesdropping on a conversation in a public place.

Surveys have shown that 83% of Australians have taken risks on-line when using Public Wi-Fi and an astounding 30% of Australians have used on-line banking over a Public Wi-Fi connection.

You should also be extra vigilant when connecting to these public hotspots, ensuring they are legitimate for the café or hotel you are in. It is not uncommon for an attacker to have a phishing hotspot setup with a similar or identical name.

Things to consider if you intend to utilise public hotspots

Use a VPN (Virtual Private Network) - to connect and secure your data. A VPN allows you to create a secure connection to another network over the internet and can shield your browsing activity and transferred data (usernames and passwords) from any malicious monitoring.

Refrain from visiting any sites which require a login with username and password, especially banking, email accounts and social media. Accessing these types of sites over a public network opens you up to potential issues which may only surface months later.

When setting up your laptop or workstation in a public area, take note to face your laptop screen away from any potential prying eyes, and monitor your surroundings over time to ensure you are the only one watching what you’re doing.

For more information on Public Wifi's and web VPN's, get in touch with one of our highly experienced staff today.