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August 15th, 2014

Data is an integral component to any business. Without it we would not be able to make decisions, develop marketing campaigns, or even operate. The issue many businesses face however is that the amount of data they generate and capture is increasing exponentially and it can be a challenge to collect and leverage it. One solution is to integrate a data warehouse, but how do you know if your business needs one?

What is a data warehouse?

A data warehouse is a system used by companies for data analysis and reporting. The main purpose of the data warehouse is to integrate, or bring together, data from a number of different sources into one centralized location. The vast majority of the data they store is current or historical data that is used to create reports or reveal trends.

Possibly the biggest benefit of a data warehouse is that it can pull data from different sources e.g., marketing, sales, finance, etc. and use this different data to formulate detailed reports on demand. Essentially, a data warehouse cuts down the time required to find and analyze important data.

While not every business will need one right this minute, a solid data warehouse could help make operations easier and more efficient, especially when compared with other data storage solutions. That being said, it can be tough to figure out if you actually need one. In order to help, we have come up with five signs that show your business is ready to implement a data warehouse.

1. Heavy reliance on spreadsheets

Regardless of business size, the spreadsheet is among the most important business tools out there. Used by pretty much every department in a company, they can be a great way of tracking data. The problem many business owners run across however is that spreadsheets can grow to immense sizes and can become unwieldy.

Combine this with the fact that each department has spreadsheets that you will likely need to pull data from in order to generate a report. If this is the case, you are creating manual reports, which can take a lot of your time.

If you are struggling to find the data you need because it is spread out across different sheets, in different departments, then it may be time to implement a data warehouse.

2. Data is overwhelming your spreadsheets

Spreadsheets are designed to operate with a set amount of data (rows and columns). Reach, or exceed this limit, and you will find that the file becomes sluggish or will downright prevent you adding more data.

While it can take a while to get to this point, companies will reach it if they keep adding to their data. At this point you will see a drop in productivity and overall effectiveness in how you use your data. Therefore, a data warehouse that can combine data from different sheets may be a great solution.

3. You spend too much time waiting

If you set out to develop a report, only to find out that you need to wait for colleagues to provide the information on their spreadsheets, or to analyze their data, you could find yourself waiting for a longer than expected time.

This makes you highly ineffective and can be downright frustrating, especially if employees are too busy or just can't provide the information needed. Implementing a data warehouse can help centralize data and make it available to all team members more effectively. This cuts down the time spent actually having to track it down and communicating with colleagues.

4. Discrepancies in data and reports

Have you noticed that when team leaders or members in different departments create reports that the data or findings are different from yours, or other reports? Not only is this frustrating, it is also time consuming to sort out and could lead to costly mistakes.

This can be amplified if some departments have data sources that they don't share with other teams, as this can throw doubt into the solidity of your data and other reports. If you have reached this point, and realize that there are discrepancies in your data, it may be time to look into a data warehouse which can help sort out problems while ensuring mistakes like duplicate data are eliminated.

5. Too much time spent generating reports

Ideally, we should be able to generate a report using existing data almost instantly, or with as few clicks as possible. If you find that when generating a report you have to keep going to different sources to check if the data is updated, or to keep manually updating other sources, you could quickly see the amount of time needed to develop a report grow.

Because data warehouses consolidate data, you only have to turn to one source for data. Combine with the fact that many data warehouses can be set up to automatically update if source data is updated or changed, and you can guarantee that the data you are using is always correct.

Looking to learn more about data warehouses, or about the different data solutions we offer? Contact us today.

Published with permission from TechAdvisory.org. Source.

July 11th, 2014

BI_July07_BAs businesses continue to become increasingly networked, there is an exponentially increasing amount of data being made available to them. While this data can be really useful, a lot of it can also be less so, or even useless. However, you are going to continue to collect data, and in order not to be overwhelmed with the sheer volume you should have a well defined data collection system in place.

What is well defined data collection?

Everyone collects data, even people who don't use computers. The key to being able to successfully leverage the data you have available to your business lies in a strong foundation - in this case, how you collect your data. With an appropriate system in pace you will know what data to collect and measure, and just how important it is. From here, you can more effectively analyze and interpret it, allowing you to make more informed decisions.

If you are looking to implement a new data collection system, or improve on how you currently collect it, here are six tips that can help:

1. Think about what customer interactions are important

Often the most important data you need is in relation to your customers. Your first step should be to define important customer interactions. For example, if you own an online store, you will likely want to know where your customers come from, the items they click on, items they add to their cart, and items they ultimately buy.

By first identifying important interactions to track, you can then look for metrics and data collection methods related to these interactions. This makes it easier for you to track the most important data.

2. Think about what behavior-related data is important

Don't just focus on those customers who have completed a purchase or followed through the whole business chain. Think about what behavior could produce data that is important to your organization.

To continue the online store example from above, this information could include how far down the page people scroll, how many pages deep they go when looking at product categories, how long they spend on a site, and where those who don't convert leave from.

Collecting and analyzing data like this can be a great determinant of what is working well and what needs to be improved upon.

3. Look at important metrics you use

Sometimes the way you collect your data will depend on how you plan to measure it. This includes the different metrics you use to define the success or failure of marketing plans, sales initiatives, and even how you track visitors.

Be sure to identify which ones your business currently uses, as these will often point you towards the relevant data you will need to collect.

4. Identify the data sources you are going to use

In many businesses there are redundancies with data collected. For example, a CMS (content management system) will often have some of the same data points as Web analytics, or a POS (Point of Sale) will have some of the same data points as an inventory system. Due to this, you are going to have to identify what systems will provide what data.

On the other hand, many businesses use data from multiple systems for one key metric. In order to ensure that you are collecting the right data, you will need to identify these sources and ensure that they are compatible with your data collecting system. If they aren't, you could face potential problems and even make wrong decisions based off of incomplete data, which could cost your business.

5. Keep in mind who will be viewing the reports

When implementing data collection systems and subsequent data analysis systems, you will likely start generating reports related to this data. It is therefore a good idea to identify who will be reading these reports and what the most important information they will need is.

This information will be different for each audience, so be sure to identify what data they judge to be important. For optimal results, you should think about who will be reading the data reports and what relevant data needs to be collected in order to generate them.

6. Set a reasonable frequency for collection and analysis

This can be a tough one to get right, especially if you work in an industry with high fluctuation or your business is in a constant state of change. Your best bet is to look at when you think you will be needing data. For example, if you are responsible to submit a monthly sales report it might be a good idea to collect data on at least a bi-weekly basis in order to have enough to develop a report at the end of the month.

You should also look at who will be getting the reports and how long different campaigns or business deals will be in place. The frequency will vary for each business, so pick one that works best for your systems and business.

If you are looking to implement a data collection system, contact us today to see how we can help.

Published with permission from TechAdvisory.org. Source.

June 18th, 2014

businessintelligence_June16_BBusiness intelligence (BI) plays a vital role in most businesses. It helps identify and monitor business trends and facilitate decision making, as well as improve your strategic management processes. Isn’t it time you made use of your company’s resources and accessed valuable corporate data to improve your BI for the good of your company success?

5 ways to improve business intelligence value

1. Pump customer data into your analysis
Most companies are chasing after a 360 degree view of their customers, and while this seems like an elusive goal, it can be achieved. Take the first steps by integrating data from your CRM, accounting, and customer support systems into your BI dashboards and reports to allow analysis of customer growth, profitability, and lifetime value.
Understanding these KPIs can help you spot trends as well as identify opportunities to cross-sell or upsell.
2. Set up alerts and delivery
Your business intelligence can instantly improve its standing and value with alerts and report delivery. Notifications, in the form of email alerts, are useful for managers to keep an eye on business operations without having to log into the BI system. The added perk here is that managers can stay on top of KPIs and new updates even when they’re on the move as reports and dashboards can be emailed to them according to a set schedule.
3. Reassess your dashboards
If it’s been a while since your BI dashboards were first designed, try updating them with modern charts and stylish fonts. While this may seem unnecessary to some companies, attractive dashboards attract more users and you’ll likely see an uptick in adoption after a dashboard refresh.
4. Deploy existing content on mobile devices
By increasing your BI content’s availability, you can quickly increase the number of users accessing it. A great way to do this is by deploying your dashboards and reports on mobile devices. This is especially useful for decision makers who travel frequently or need to be able to access KPIs from anywhere; after all it’s easier for them to pull out a phone or tablet rather than drag out a laptop. Your BI system likely includes some way to make your existing BI content mobile. Allowing users to access BI the way they want can be a great way to boost your BI value.
5. Make it predictive
While BI has traditionally been used to present historic data for manual analysis, now more than ever it’s incorporating predictive analytics. By leveraging stored data from your BI system and applying predictive analytics, you can project future performance and make better business decisions based on more accurate forecasts.

Modern BI platforms come with many options, from multi-data source connectivity to mobile BI. It is up to you to leverage the full breadth of your BI software’s capabilities to ensure that you’re getting all the value it can deliver. Looking to learn more about business intelligence and its functions? Get in touch.

Published with permission from TechAdvisory.org. Source.
May 23rd, 2014

BI_May19_BIn business, it would be great if we could tell what the future holds. And although we can't predict 100% for sure what will happen, businesses do have a set of tools at their disposal that can help foretell more than a wild guess. The most popular forecasting tool is predictive analytics. While it is employed in many organizations, small business owners are beginning to look into it too.

What is predictive analytics?

Before looking at why businesses might want to implement this type of analytics into their operations, it's worthwhile defining what exactly predictive analytics is. Simply put, predictive analytics is a form of business intelligence that focuses on combing existing information for patterns and useful data that can then be used to make predictions on future outcomes or to identify trends.

It is important to stress that this form of analytics does not tell you what is going to happen. Instead, it is used to figure out what might happen. Think of it as similar to a weather forecast for your business - meteorologists can never tell you what the weather will be like over the next week, they merely use the data they have at their disposal to forecast what the outlook is likely to be in the next few days.

The vast majority of companies who apply these analytics to their business often do so to gain a better understanding of their customers, partners, and other stakeholders. From this they can better identify possible risks and opportunities.

Five reasons to use predictive analytics:

  1. Compete better - Companies who use predictive analysis can generally compete smarter. This is because they can leverage existing data to figure out why their customers choose them. By doing the same, you can then focus on highlighting your strengths. This is especially useful if you have some quality strengths to play with.
  2. Work out how to better meet demand - If utilized effectively, you can predict with some accuracy the level of demand for your products, including sales of specific items at certain times, and high/low times for customer visits. From here, you can schedule deliveries or staff to ensure products and staff will be available.
  3. Exceed expectations - While forecasting customer demand is important, what really keeps customers returning is when you exceed their expectations. One of the best ways to do this is by offering products or services the customers need them; or even before they need them or know they do. By understanding customer buying habits you can develop individualized campaigns that focus on their upcoming needs; offering useful products and/or services.
  4. Increase efficiency - Analyzing your existing data can help predict when you may have supply issues, or where production problems may crop up when launching a new product or service. With this warning system in place you can take steps to limit any negative repercussions or make provisions to guard against a predicted problem. This then can help increase overall efficiency.
  5. Better able to reach clients - By first tracking customer touchpoint data - when did they contact you and how - you can then use this data to forecast when your customers will be looking at social media, more willing to read an email you send, and even when they might be more willing to talk with you on the phone.
These are just a few of the reasons businesses use predictive analytics in their companies. If you are curious to learn more about how to create success for your business and the technology systems that support and allow you to utilize predictive analytics, contact us today for a chat.
Published with permission from TechAdvisory.org. Source.

April 26th, 2014

BI_Apr22_BBusiness Intelligence (BI) is quickly becoming one of the most integral functions for many small businesses. Owners and managers are increasingly finding that by implementing BI functions they can make better and more informed business decisions. While BI is popular, there are however many misconceptions that could actually inhibit the effectiveness of your efforts.

But many of these misconceptions are easily clarified and addressed. See how by taking a look at these tips.

1. Business Intelligence is all about reports and dashboards

One of the things that make business intelligence sound intimidating is the notion that businesses will be bombarded with daily reports and have to make use of complicated dashboards in order help to understand how it works and get it operational. While there are standard tools that small businesses will need to use to gather information that will help with their operations, these tools should not be seen as an inconvenience. The systems and processes in BI can be simplified in a way that it doesn’t limit resource gathering but actually enhances efficiency and profitability.

An executive, for instance, can easily look into the sales numbers of a given month, without having to go over other variables and metrics. Other models of BI can cater to more than just reporting stats and data, as analysis can be collaborative and interactive, thus providing more efficient solutions that will deliver the correct information to the people who rely on the data for their decision-making.

2. The tools are the same for all organizations

The assumption is that whether a company is big or small, the tools in business intelligence work the same. This is what makes small businesses hesitant to apply such concepts, thinking that it will not have any practical use in an organization of their size.

But the truth is, every BI strategy is unique, and as a company, you can tailor these strategies to fit in with the way you operate. Before adopting any solution, however, you will first have to evaluate what specific needs BI must address using the data architecture, so that it will measure your requirements correctly.

3. It can only measure big data

Large corporations can maximize the tools to use in BI because they have larger needs to fill, and they also have all the resources. But what about small companies that may not necessarily need big data?

The thing is, any company that has data will have a use for business intelligence. Small businesses can start with simple and basic solutions, for instance Google Analytics, and then later on, expand to a more comprehensive tool as the organization grows. Business intelligence measures the quality of data, and not the quantity, so you can accomplish something even with very few resources.

4. It takes up IT resources

While BI used to be considered the responsibility of an IT team or expert, now small businesses, which may not have had the resources to in the past to outsource such resources, can use the tools for themselves. There are solutions out there that offer low maintenance, self-service systems wherein reports and dashboards are created and analyzed without the need for an IT expert whatsoever. There are some advantages to having professional IT help sometimes though, but for small businesses, a user-friendly BI system may be sufficient to cover most of your needs.

If you'd like to know about how you might be able to develop your business intelligence systems further. Consult a reputable IT services provider now.

Published with permission from TechAdvisory.org. Source.

March 28th, 2014

BI_March24_BSeveral companies nowadays rely on Business Intelligence or BI tools to analyze information generated by their business. These tools are either installed on computers or cloud-based and accessible on the Web. These applications allow users to ensure that everyone is on the same path with regards to achieving their business goals. The question is, how are different departments using 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.

March 1st, 2014

BI_Feb24_BIf there is one thing all businesses rely on it's data. As the integration of new systems and features continues, the amount of data available to a businesses grows. In order to be able to get more out of this data, businesses have started looking at adopting Business Intelligence (BI) systems. These come with their own language, and three of the more confusing terms are 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 31st, 2014

BI_Jan27_BData has always been one of the most essential components of any business. Without data, many businesses would be unable to make essential decisions or even track their success. For companies that track this, they have likely heard of business analytics. While this term is popular, it can be confusing to actually nail down what this is.

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 4th, 2014

BI_Jan02_BBusiness Intelligence - the collection and transformation of data into useful information that can be used to make better decisions - is one of the more important business processes, and saw continued popularity in 2013. Because of this increased use, there are a number of trends that we believe will be become favorable in 2014.

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 6th, 2013

Bi_Dec02_BIt's not uncommon for established small to medium businesses to hit a bit of a wall when it comes to sales and growth. Often, after a period of great growth, businesses can begin to see sales and profits level off. This stabilization can be tough to break out of, especially if you want to continue growing. One way businesses can break the cycle though is by analyzing existing data to identify 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.