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March 27th, 2014

BI_March24_ABusiness Intelligence, or BI, refers to the processes and systems involved in the collection of business information for analysis to determine the past and current status of your company. It serves to give a better insight into what is about to transpire. Many companies from different industries use BI tools in their business, but the question is how can different departments use them?

There are various BI tools available nowadays that support small to large companies. You can find Business Intelligence tools that fit your company’s size, needs and budget. These applications can be used in different areas of the business:

Marketing Department

A marketing department is responsible for promoting a company’s products, services and brand to increase public awareness. With successful marketing, a business can attract potential clients that can be possibly turned into creating sales revenue. The company can use BI to determine which campaigns are successful or not, as the case may be. Through this, investments can be focused on those campaigns that work whilst avoiding those that have previously failed.

Sales Department

Sales managers and supervisors can also use BI to analyze successful deals, as well as those that they have lost, to see what strategies have worked. The system can also help determine which sales teams hit or exceed set goals in order to analyze what they are doing right. Moreover, this helps determine which products or services are most saleable so these can be pushed further to attain more goals.

Finance Department

BI software makes analyzing, reporting, and managing financial data more convenient. Those who are involved in the process can easily access the information they need through the system. Analysis is easier as the data is organized and accurate. Money in and money out can also be tracked with greater efficiency.

Moreover, these tools often come with features that allow users to create scenarios and determine the possible results from there. This is extremely helpful in deciding on the best action to take as the tool gives you a view of the probable outcome. The success rate is higher if forecasting using a BI tool.

Inventory

Business Intelligence also plays a vital role in inventory tracking of products, items or supplies. For instance, companies in the retail industry can track the movement of products or items from the suppliers to the warehouse and on to their delivery to clients. Any problems encountered in the process can be quickly identified so they can be fixed in time.

Items in demand can also be pinpointed, as well as low stock and overstocks. Items that are low in stock can be ordered immediately, especially if they are in demand, to ensure that the needs of clients are met. This also lets you avoid overstocking, which can be a waste of money when investment is better used for fast moving items.

These are just some of the ways businesses can use BI in their operations. If you have further questions about the topic, do not hesitate to give us a call. We’ll be more than happy to assist you.

Published with permission from TechAdvisory.org. Source.

February 28th, 2014

BI_Feb24_ABusiness Intelligence (BI) has become an essential function of many businesses. Those who employ some form of BI often see increased sales, or at the very least the ability to make quicker informed decisions more often. When looking into BI solutions however, you will likely come across a number of terms that may be a little confusing. Three of these somewhat puzzling terms relate to data - data mart, data warehouse and data mining.

What is a data warehouse?

The concept of a data warehouse is an interesting one and also a difficult one to define and pin down largely because it can cover such a broad area. The most concise definition we can give is that it is a database that integrates data from many different locations and databases into one consolidated database.

Data warehouses store both current and historical data, and rarely contain unique data. Instead, they aggregate data from other sources in order to make this more accessible. They might store important information from sales, marketing, ERP, customer interactions, and any form of database in order to quickly generate BI related reports.

The name undoubtedly conjures up the idea of a large warehouse-like building storing infinite amounts of data. However, most data warehouses are actually tables which are created by taking data from various sources and cleaning it up so that relevant data is stored in the warehouse in a way that makes it easier to reach when needed.

What is a data mart?

A data mart is a smaller data warehouse that stores data. These are based on a specific area or business function e.g., finance or marketing, etc. In fact, most modern data warehouses are actually made up of a series of smaller data marts.

The key difference between a data mart and a data warehouse is that data marts are usually smaller, focusing on one specific area, while a data warehouse covers the whole organization.

What is data mining?

When talking about Business Intelligence, many experts will refer to data mining. This is the act of analyzing data in order to identify patterns. The data that is mined can then be transformed into useable information. Many companies store this mined data in databases, a data warehouse, or a data mart.

Want to learn more about these terms and how your company can benefit from a BI solution? Contact us today.

Published with permission from TechAdvisory.org. Source.

January 30th, 2014

BI_Jan27_AIt seems like over the past five years or so, understanding, processing and leveraging of data has become one of the most important parts of a business. When reading about data you often come across the term 'business analytics'. Despite this terms common usage many people are confused as to what exactly it is and where exactly it fits into business processes.

In this article we will take a brief look at business analytics and why it is so important to businesses of all sizes.

Business analytics defined

When experts talk about analytics most audiences will agree that it is the analysis of data and statistics. The vast majority of business owners have some experience with analytics, with some having even taken courses on it at University. This being said, the idea of business analytics is often hard to pin down - ask 10 people and you will likely get 10 different answers defining what exactly it is.

We like to define business analytics as a process rather than a science. This process uses skills, business experience, technology, applications, and common business practices, to enable business owners, managers, and employees to explore past performance. Simply put, it's the study of the past performance of a business.

With most businesses, the goal of business analytics is to gain insights into the state of the company, and even drive future decisions based on existing data. If you can successfully implement a business analytics process, you and your employees will gain a higher understanding of your business which will lead to better decision making abilities and even higher growth and profits.

What makes up business analytics

As we noted above, this is a process that involves a number of separate components. Four to be exact:
  • Analytics - Using modern data mining and predictive tools to identify patterns that can help make better business decisions and give managers foresight into potential future trends. Usually the questions answered include, "What is the best outcome?", "Why did this work?", etc.
  • Data management - This covers the collection and storage of data. Concepts include how and where the data is stored, who has access to it, how it is accessed, and even when it can be accessed. Some examples of this include using cloud-based storage or even a storage server that is hosted in the office. When looking at data management in terms of analytics, most managers will concentrate on what has worked in the past, why it worked, and what will work in the future.
  • Business Intelligence - This is the use of reporting tools and dashboards to gain an understanding of largely event-based questions like, "How many?", etc. When you implement business intelligence operations you will normally gain better insights into current events and what happened in the past to influence them.
  • Performance Management - This broad term covers actions and tools that are used to track and manage business performance. This includes tasks such a financial reporting and budget forecasting.
The main reason businesses implement the components of business analytics is so that they have a way to not only harness the data their business generates, but to also leverage it in a constructive way so that their business can make better decisions. If used properly, it really helps businesses answer two of the hardest questions to answer: "What do I need to know?" and "What do I need to do?"

If you are looking to learn more about using business analytics or the components that make up this process, contact us today to see how our solutions can help.

Published with permission from TechAdvisory.org. Source.

January 3rd, 2014

BI_Jan02_AIn 2013, Business Intelligence - transforming data into useful information that can be used by managers to make decisions - has become a popular process used by businesses to make better decisions. Because this has become such a popular and important business function, you can bet that you will continue to hear about it in 2014. The only question is what exactly will be the latest developments this year?

Here is an overview of the potential Business Intelligence (BI) trends we could see emerging and growing in 2014.

1. BI is more accessible

Historically, to get the most out of Business Intelligence you need to be experienced or to employ a data scientist. Over the past couple of years BI methodologies have become easier to execute. Throughout 2014 it is highly likely that we will see most ordinary business users continue to gain skills in this area and consequently carrying out business analysis and BI activities.

This means we should see an increase in the number of programs that are user-friendly, while still providing the powerful tools that experts have been using.

2. BI and Big Data solutions forecast clouds

Cloud-based solutions have helped allow small to medium businesses to access tools that were previously only used by enterprises. Many BI solutions are starting to incorporate cloud-based versions and this trend will undoubtedly continue in 2014.

These solutions will put important data in the hands of individual businesses, while also providing them with the ability to store and analyze their data with ease, as long as they have an Internet connection. Many of these solutions also allow for increased collaboration and some even have mobile apps which could help make adoption easier.

3. Predictive analytics are more accessible

Predictive analytics is the process of looking at existing data for trends and important information that you can use to help make predictions and decisions. This type of analysis has largely been the domain of experts and large companies, but in 2014 this process should become increasingly available to small businesses.

4. Social data is even more important

The majority of customers are active on social media. This has led to a huge source of potential information that businesses can benefit from. From Likes to Shares, Comments, etc., companies will begin to pay closer attention to this data. It can help businesses gain insight into brand awareness, how relevant they are to customers, and even gain important information they can use to conduct competitive analysis.

5. Storytelling from existing data

One of the main objectives of analyzing your data is so that you can tell a story with it. If you have no narrative arc attached to your data, it is highly likely that the message you want to get across won't sink in.

By visualizing your data in a way so that it tells a story you will be better able to gain a concise meaning from an overwhelming amount of data

If you are looking to learn more about BI and how it can help your business, please contact us today.

Published with permission from TechAdvisory.org. Source.

December 5th, 2013

Bi_Dec02_AMany small businesses, even when they are an established company doing well, can encounter problems and run into a wall, blocking progress. Profits can level off and growth or sales can start to level out. This creates stagnation which can be a difficult challenge to overcome, especially to those who are risk averse. One way companies might overcome these issues is by analyzing existing data in the organization and looking for patterns.

In order to move your business forward and grow, you should analyze and try to interpret the data in your organization. This includes everything from previous financial statements, year-on-year sales figures and numbers, and even KPIs or estimated Vs actual figures. By looking into this data, you will eventually begin to find patterns which can be useful in not only helping you figure out the current state of your company, but in identifying where it is going.

Why should you analyze data for patterns?

Most experts agree that there are four reasons businesses should be analyzing their data:
  • You can better evaluate past performance.
  • You can assess current status.
  • You can more accurately predict future potential.
  • You can make better decisions that will maximize profits and resources.
Essentially, when you track and analyze your data you should be able to spot potentially important patterns that can allow you to make better decisions, quicker, and usually with more accuracy. It is the analysis of patterns that also makes up an important part of Business Intelligence.

What types of patterns should you look for?

Many small to medium businesses generate a wide variety of data, and it can be a challenge to narrow down what data types and patterns to look for. To start with, many businesses focus on three main patterns:
  1. Industry comparisons - By looking at the financial information from other companies in your industry, you can detect overall industry performance and identify any anomalies. For example, if some companies have increased sales and profits, while others are static or decreasing, the more successful businesses may be doing something that you can also adopt in order to improve your sales.
  2. Actual vs planned performance - By looking at your actual and planned sales you can see how the company is doing e.g., were sales lower than expected? If yes, you can begin to look into why. When compared year-over-year you should be able to see patterns emerging that help you resolve issues or take advantage of new opportunities.
  3. Trend analysis - This is comparing current and past performance with the aim of finding out where or how your business has changed. Some examples of patterns are how sales are trending, how profits are doing, and cash flow. From here, you can determine how differences have occurred and what corrections are needed.

How do you analyze data and identify patterns?

Many businesses rely on spreadsheet software, such as Excel, to store, manipulate, and visualize data, to ultimately spot patterns. But this requires a fair amount of effort to establish and maintain, and as the spreadsheets grow, operations can slow down.

One option many businesses explore is utilizing Business Intelligence software, which allows businesses to easily track data and identify patterns, among other uses. There are a wide variety of programs, so if you are looking to begin tracking data and analyzing patterns, try contacting us today to see what solutions we have for you.

Published with permission from TechAdvisory.org. Source.

November 5th, 2013

BI_Nov05_AThere’s no shortage of data for the small business owner. Whether you hire a professional industry analyst to look at your business information, or do it yourself, statistics and reports can reveal valuable information. But making sure that information is enriched with knowledge is the difference between having numbers to hand and having vital data that could transform your business.

Many small businesses depend on their IT personnel to provide data that will enhance their business. However, there’s a difference between mere data and enriched information that improves performance. For instance, you might be surprised to find that page views are largely useless. This figure tells very little about how people are actually using your site, which is the most important information you can have. Data that leads to improvements is more than just information. It’s intelligence. There are many types of information which can help businesses become more intelligent.

Visitor flow Visitor flow follows how users navigate your website. The most important point is to learn about where your customers enter your site, and where they leave. Simple numbers of visitors is not as useful. Let’s say that you are running an online store and that 350 visitors left your site on the 'confirm order' page. This might suggest there’s some type of sticking point related to this page. It might be that the wrong orders are loading. It might be that a sudden tax add-on that wasn’t fully clarified caused users to cancel the purchase. Regardless of the reason, this type of business intelligence may help you make positive changes in the online experience you create.

Traffic sources Traffic sources tell you where your customers are coming from and therefore what’s driving people to your site. Wouldn’t it be helpful to know the type of sites which are leading to yours? With that information, you might step up advertising and marketing within those sites, and bring even more business your way. Traffic sources are also a great way to measure the effectiveness of advertising.

Keywords When you know what keywords people use to find your business online, you can begin tailoring your pages to contain more of them. You can also begin applying those keywords in advertisements, banners, and promotional efforts you invest in online. By better meeting user desire and expectation you can raise your profile above that of competitors.

Conversion rates Your business makes money when people buy your product or services. Conversion rates can help track users through the entire sales experience. By finding out key data about where users spend time online, where they enter the sales experience, and when they leave, you are better able to adjust your product or service, your presentation, and perhaps your website design. By finding peak points of purchase, you can pinpoint successful pages or links too. By finding weak points of purchase, such as abandoned online shopping carts, you might be alerted to tech problems or layout aspects that interfere with more robust conversion rates.

Bounce rates Bounce rates reflect the number of users who visit your site but leave without looking at any other pages. In a best case scenario, it means they find what they are looking for on your site fast. In the worst case scenario, it means that your users lose interest immediately, and big changes on your site have to be made. A high bounce rate can be changed through rich content development that engages users to remain within your site, exploring what your business has to offer in terms of products and services, and more.

Bounce rates are a great example of the difference between metrics and information. IT might present stats that show 3,000 people are visiting a site each day. This might seem like good news, until it's revealed that the bounce rate is 2,999. This is the difference between information and intelligence.

Business intelligence creates a better opportunity to maximize your production and profits. We can help in that process, so get in touch today.

Published with permission from TechAdvisory.org. Source.

October 11th, 2013

BI_Oct08_AThe path to running a successful business starts with making the right decisions. This can be a challenge for many business owners, largely because nobody can see what the future holds. This is why Business Intelligence (BI) has become so popular; it helps us make better decisions. One form of BI is visualization - taking data and turning it into something visual we can use. While this can be useful, there is a chance that it can lead to data being misrepresented and the wrong decisions being made.

Here are four tips on how to make successful data visualizations - e.g., charts, graphs, flowcharts, etc.

1. They need to be easy to understand When visualizing data, it can be very easy to make the outcome incredibly confusing. By having too many sets of data, trying to compare and visualize too much, or by simply laying information out in a confusing way, you could actually decrease the effectiveness of the message you are trying to convey or lose it altogether.

When creating visualizations, try to get someone who is part of your target audience to look over it and make sure they can understand what the visualization is representing and that it is easy to comprehend. If they can't, you need to go back to the drawing board and try to come up with a way to present the data where the intended audience can understand and follow it easily.

2. They need to cater to the audience The main reason most managers or owners visualize data is to present it to an audience. 99% of the time, this audience is a decision maker and you are trying to get them to decide on whatever the data visualization is representing.

Therefore, when setting out to visualize your data you should first define an end goal - what you want the audience to do with the data. In order to do this, and to develop a successful visualization, try considering these three questions:

  1. Who exactly is the audience? - Because the audience will ultimately be making the decisions, you should define who they are. Focus on how much they know and how comfortable they are with the subject, and their position within their organization or outside it. From there you can begin to tailor which data to present and how.
  2. What does your audience expect from the data? - This can be achieved fairly simply by actually asking key members of your audience. Try reaching out in an email and asking about their expectations. If they say they want something simple to understand, don't use overly complex graphs or visualizations. Focus on what type of information is most important to them. For example, if you are visualizing sales data for a finance team, marketing related data may not be overly relevant.
  3. What is the role of the visualization? - Visualizations have many roles. Some are intended to educate, while others are aimed at prompting the audience to act or ask questions. As a general rule of thumb, educational visualizations should not create questions, while actionable ones should.
3. They need to have a clear framework or layout When visualizing data you need to ensure that you develop a layout or framework that is clear and easy to follow. This means focusing on two main areas:
  • Semantics - The meaning of the words and graphs used. Remember that simple words like 'or', 'and', etc. can drastically change the meaning of a sentence and possibly make it unclear. Because of the visual nature of this method you will need to be crystal clear with accompanying words and titles. The same goes for the visual side. If you are using icons or images, they need to look like the data they are representing and be clearly identifiable as different from other sets of data.
  • Syntax - This is more how the words and visuals are used and represented. If visual and accompanying words are not laid out in a clear and logical manner, there is a high chance that the message or action you want to convey will fail to be grasped. Also, pay attention to how you present the data. If you are using a graph with lines, most people will view this as trend related, even if you intended to compare the results to different sets.

Above all - They need to tell a story The most successful visualizations tell a story about the data. Unlike TV or movies, you aren't telling a story for pure entertainment. The story should be related to how the audience will be affected or can be helped by the data represented in the visuals. If you are struggling to find a way to tell a story, try actually explaining the data. By knowing it inside and out, you will likely be better able to come up with an explanation that you may be able to weave into a fluid story for your audience.

If you are looking into visualizing your data, or improving how you present it, why not contact us to see how our systems can help.

Published with permission from TechAdvisory.org. Source.

September 13th, 2013

BI_Sep09_AA popular trend related to data is the increasing use of infographics and visualization. While it is true that a visual representation of data can be helpful, it doesn't mean that every bit of data collected needs to be represented visually or turned into an infographic. So, when exactly should data be visualized?

In order to know when data visualization should be used, it's a good idea to start with why we even use it at all, and what makes it work.

Why visualize data The whole point of taking data and turning it into more understandable information is so that we can utilize it to make a decision or take action from what we learn. Data visualization is just another way of turning data that we can't read or understand and turning it into something that we can see and use. In other words, creating information with visible insights.

In general there are three reasons why you might want to visualize data:

  1. Education - Many visualizations are valuable because they educate or report on a specific topic. These can also provide insight into changes related to a topic over time, so that you are able to understand trends and learn from them.
  2. Exploration - As more data sets become increasingly larger, it can be tough to easily spot relationships between them and create predictions. Visualization can make this easier to understand and manage.
  3. Confirmation - If there are assumptions about a subject, and data has been collected, visualizing it can be a useful way to prove or disprove the assumption.
What makes a good data visualization There are three main aspects of information that make up good effective data visualizations:
  1. It's interpretable - With the sheer amount of data available to managers and owners you can be sure that some of it will be useless. It could be the data collected doesn't have enough relevant information, such as where it comes from, when it was collected and by whom. If you can't interpret data, you likely won't be able to gain insight from it which makes it hard to actually visualize what information it is you have.
  2. It's relevant - The data shown needs to provide valuable insight to the audience and therefore needs to be relevant. Beyond that, it also needs to align with the overall purpose of why it's being examined.
  3. It provides something new - Above all, the visualized data should show some new findings or provide insight that you did not know before.
If the visualization fails to meet any one of these three aspects, you will end up with an outcome that doesn't provide value and will likely be ignored or viewed with skepticism. In this case it is probably not worthwhile trying to visualize it.

If you would like to know more about how you can visualize data, or how you can harness the data in your organization, contact us today to see how we can help.

Published with permission from TechAdvisory.org. Source.

August 15th, 2013

BI_Aug09_AThe amount of data available to a business is exponentially increasing, and many are starting to realize that they can harness this for help making decisions, predicting trends and outcomes of other business initiatives. This capture and analysis of data is commonly referred to as Business Intelligence (BI) can be incredibly useful, however it isn't easy, many businesses make mistakes that could be costly.

Here are four of the most common mistakes businesses make with their Business Intelligence efforts.

1. Not involving all stakeholders When developing BI initiatives, companies will often forget to talk to all of the stakeholders who are involved in, or affected by, the initiative. You should take steps to consult with the parties and end users involved. Get to know their problems, desires, and what they plan to do with the data and information gained.

Once you know what the users need, you can look into developing and implementing the tools that will get the desired result. It is especially important to involve the people who will be implementing BI tools as they may have insight into what is needed, or how existing systems will fit/work with the intended systems.

2. Unclear goals As with almost everything else in business, you need to have a set goal as to what you want to achieve with the project, tool, initiative you are implementing. If you don't know what you want your BI to do, how it is to be presented or even why, you will likely run into problems that could lead to the wrong decisions being made, or even lost profits.

It would therefore be a good idea to sit down with the teams and stakeholders to see what they want, and set goals as a group. Then look for a solution that will meet these needs and goals.

3. Using the wrong tools Just because other companies have implemented BI, or a specific tool, and have had success, doesn't mean you will. Some companies have done excellent work getting buy-in from all teams and user needs and goals are clearly defined, but when they start looking for tools, settle for something that is merely good enough.

This will hurt them because the tool may be missing key features that parties want. Also, like everything else in business, BI will change over time and if your company's goals change and the tools can't keep up with it or support it, you could be looking at costly changes, or inefficient decision making support.

4. Team members lack skills Technology is always changing and companies are always implementing new systems. Because BI is tool based, you will have to add new technology, and guaranteed the users won't know all of the ins and outs. Therefore, they will need to be trained on how to use them.

If the users don't know how to use the tools, data could be collected inefficiently, the wrong data may be collected and analyzed or the wrong outputs could be produced. What this means is ultimately lost profits for you.

These are the common mistakes made by business in regards to their BI. If you are looking for a solution that will help ensure that you avoid these mistakes and get the data and answers you need, contact us today to see if we have the right one for you.

Published with permission from TechAdvisory.org. Source.

July 18th, 2013

BI_July15_AWhen it comes to making important business decisions, often the most successful ones tend to be those made utilizing solid knowledge, sound experience and reliable data. Much of this valuable information is now gathered and stored in computers, and the use of this has given rise to Business Intelligence (BI). One new form of BI that is fast gaining popularity is Big Data.

You've likely seen or heard the term Big Data, but do you know what it is? Here is a simple definition, along with some examples and ways businesses can use it.

Define: Big Data If you search for definitions of Big Data, you will likely come across something along the lines of: Big Data is data that focuses on harnessing and using new forms of unstructured data that move into or through a business with high volume, velocity and complexity.

But what exactly does this mean? Well, many find this definition vague, at best. We found a definition, an equation in fact, that better explains Big Data: Big Data = Transactions + Interactions + Observations

Transactions This is highly structured data related to events. It always includes: Time, a numerical value and refers to an objective, or objectives. Examples of this include, invoices, travel plans, activity records, payments, etc. The vast majority of this information is stored in databases and can be accessed quickly and easily, usually through SQL (Structured Query Language).

Interactions This covers how people interact with one another, or with your business. This includes interactions such as Facebook posts and Likes, social feeds, generated content and even blogs. Basically, this encompasses any data you can collect through any type of interaction that this isn't limited to business transactions. Many experts expect this part of Big Data to really take off and become more valuable as social networks become ever more integrated with our lives and the corporate world.

Observations This is information gathered from the Internet of Things. The Internet of Things is associated with unique, individual things that have a virtual component that can be observed, and are connected in an Internet-like structure. Some examples of this include GPS coordinates from a person that visits your website on their mobile phone, or RFID chips in ATM cards. This data can be stored and potentially used to make better, more informed decisions.

When you combine these three things together, along with the data associated with it, you get Big Data.

Some sources of Big Data Here are just a few of sources of Big Data:

  • SMS messages
  • GPS coordinates associated with mobile interactions
  • HD video, audio and images
  • Product logs
  • Affiliate networks
  • Purchase details
  • Facebook Likes and shares
Ways business can use Big Data There are numerous ways small to medium sized businesses can employ Big Data:
  • To provide better service - You can use Big Data to better tailor products for individual customers based on their buying habits, Facebook Likes and even personal preferences such as favorite colors.
  • Identify key customers - It can be hard to identify who your key customers are, especially if your company has a large customer base. By using Big Data, you can better identify who your primary customers are and their demographics. This makes it easier to make customer oriented decisions and marketing strategies.
  • Identify new business opportunities - If your company is harnessing Big Data, you will be better able to spot upcoming trends and better equipped to predict if these will prove popular.
  • Identify potential problems - If you monitor social media feeds, incoming calls and forums, you should be able to pick up potential problems more quickly and easily. This gives you the chance to fix issues before they escalate and cause any damage to your business.
There are many uses of Big Data, and as the world continues to generate more and more data, it will become increasingly important to employ Big Data techniques in your business. If you are looking to learn more about this topic, or any other part of Business Intelligence, please contact us today.
Published with permission from TechAdvisory.org. Source.