Carrollton Dermatology Associates
Dr. Thomas H. Lamb, MD.
Brighter Image, Inc.
RA-Lin and Associates
North Georgia Turf, Inc.
With the steady increase in the adoption of business intelligence suites and solutions by small to medium businesses, managers and owners have been able to take advantage of better data. One business function that has really benefited is sales. There are so many sales-related metrics to employ, it can be tough to actually pick the ones that work for your business. To help, here are five of the most common and most useful sales metrics.
When companies set up their sales pipeline metrics they often set out to measure:
Beyond giving a useful whole-business overview, this metric can also uncover exactly how much each sale influences or contributes to the bottom line. This can be calculated by using the standard profit-ratio equation - net income over sales revenue.
From here, you can track improvements and tweak forecasts to ensure that they become as accurate as possible. After all, if you can show that you are meeting your goals, or are close to meeting them, you can make more reliable decisions and be assured that your company is doing as well as it appears to be.
While a high rate is preferable, low win rates are also useful largely because they can highlight areas where improvement is needed. For example, if your team has constantly low win rates across the board, then it could signify that there is a need for more training on closing sales, or that sales staff may not be knowledgeable enough about the products or services being offered. A fluctuating rate could show increased industry competitiveness and highlight when a sales push could be beneficial.
Essentially, when measured correctly, you can use loss rate to improve the overall sales process and hopefully bump up your overall win rate. You can also compare the two rates to really see how big of a gap there is and give your team a solid goal to try and find ways to reduce this gap.
If you are looking for solutions that allow you to track and measure your sales and any other data you generate, contact us today to learn how we can help turn your data into valuable, viable business information to lead your company to better success.
When it comes to running a business, you likely thrive on customer and employee interaction. If your customers aren't active, or employees are struggling to interact with each other and customers, you could be facing a downward spiral. One way companies try and reverse this stagnation, while simultaneously gaining important and useful data, is through gamification.
By implementing game elements into areas like marketing or training, you can drive engagement, while also collecting better data, primarily because most people will be more willing to provide relevant information when they are invested in a game.
When it comes to implementing these elements into business processes, many companies tend to focus on either customer gamification or employee gamification.
Many businesses have been successful in implementing this game characteristic into social media, where people who interact gain levels and therefore access to such benefits as discounts. Businesses implementing customer-oriented gamification often see both increased engagement and better data flowing into the organization. In fact, many businesses have found that the data implemented through these elements has been useful in decision-making and overall business intelligence efforts.
As with customer gamification, employee gamification can be a great source of data. For example, by tracking where employees are, and their results, you can quickly see weak spots or places where help may be needed. Essentially, more data means the ability to make better decisions.
If you find that gamification, or elements of it, won't benefit your business program, then it's best not to implement it for the sake of it.
In business, as in life, we constantly try to make predictions about the future. How will sales be next year if we implement a new procedure? What will the weather be like for the annual staff event next week? It's no surprise then that businesses of all sizes have started to embrace the idea of predictive analytics. However, many business managers are unsure as to exactly how to work with this form of analytics effectively. To help, here is an overview of the three main components of predictive analysis all business owners and managers should be aware of.
Together, these three elements of predictive analytics enables data scientists and even managers to conduct and analyze forecasts and predictions.
If you want predictive analytics to be successful, you need not only the right kind of data but information that is useful in helping answer the main question you are trying to predict or forecast. You need to to collect as much relevant data as possible in relation to what you are trying to predict. This means tracking past data, customers, demographics, and more.
Merely tracking data isn't going to guarantee more accurate predictions however. You will also need a way to store and quickly access this data. Most businesses use a data warehouse which allows for easier tracking, combining, and analyzing of data.
As a business manager you likely don't have the time to look after data and implement a full-on warehousing and storage solution. What you will most likely need to do is work with a provider, like us, who can help establish an effective warehouse solution, and an analytics expert who can help ensure that you are tracking the right, and most useful, data.
Using data that has been collected from various customer touch points - say a customer loyalty card, past purchases made by the customer, data found on social media, and visits to a website - you can run a regression analysis to see if there is in fact a correlation between independent and dependent variables, and just how related individual independent variables are.
From here, usually after some trial and error, you hopefully can come up with a regression equation and assign what's called regression coefficients - how much each variable affects the outcome - to each of the independent variables.
This equation can then be applied to predict outcomes. To carry on the example above, you can figure out exactly how influential each independent variable is to the sale of product X. If you find that income and age of different customers heavily influences sales, you can usually also predict when customers of a certain age and income level will buy (by comparing the analysis with past sales data). From here, you can schedule promotions, stock extra products, or even begin marketing to other non-customers who fall into the same categories.
As a business owner or manager you are going to need to be aware of the assumptions made for each model or question you are trying to predict the answer to. This also means that you will need to be revisiting these on a regular basis to ensure they are still true or valid. If something changes, say buying habits, then the predictions in place will be invalid and potentially useless.
Remember the 2008-09 sub-prime mortgage crisis? Well, one of the main reasons this was so huge was because brokers and analysts assumed that people would always be able to pay their mortgages, and built their prediction models off of this assumption. We all know what happened there. While this is a large scale example, it is a powerful lesson to learn: Not checking that the assumptions you have based your predictions on could lead to massive trouble for your company.
By understanding the basic ideas behind these three components, you will be better able to communicate and leverage the results provided by this form of analytics.
If you are looking to implement a solution that can support your analytics, or to learn more about predictive analytics, contact us today to see how we can help.
The amount of data both available to, and generated by, a company is increasing exponentially. While some smaller to medium businesses are coping fine with the growth, many are struggling with managing their data, let alone leveraging it to help make better decisions. If you find that your business isn't coping with data, one solution may be to implement a data warehouse.
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.
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.
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.
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.
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.
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.
As businesses of all sizes continue to integrate more technology, the amount of data available to companies will grow exponentially. However, not all of that available data will be important or even useful. And, as you collect more and more data, it will be harder to process and analyze it without becoming overwhelmed. In order to avoid this, you should ensure you have a well defined data collection system in place.
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:
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.
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.
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.
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.
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.
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.
Many businesses pay between USD $100 thousand and $1 million for their business intelligence (BI) system. And yet a lot of corporate data isn’t accessed by BI users which raises the question: How important is BI to your business? The simple answer is that it is very important. From analytics to complex event processing and benchmarking, if used efficiently BI can play a major part in the success of your company. With that in mind, it is time you squeeze every last drop of value out of your BI platform to help push your business towards the finish line.
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.
Growing up we are constantly told that predicting the future is at best mere guess work, and there is no real way to tell what our future may hold. While this may be the case for much of life, in business there are ways to make accurate forecasts. One option at your disposal to be able to do this is predictive analytics.
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.
Business Intelligence (BI) is hardly a new concept for small business owners, with a growing percentage of business owners utilizing it in their business. But even so, there are a great many misconceptions that still proliferate about the theories and technology behind it and people often don't realize how they can benefit from incorporating a little BI into their operations.
But many of these misconceptions are easily clarified and addressed. See how by taking a look at these tips.
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.
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.
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.
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.
Business 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:
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.
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.
Business 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.
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.
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.
Want to learn more about these terms and how your company can benefit from a BI solution? Contact us today.