Currently viewing the tag: "Information"
Wikipedia defines Forecasting as the process of making statements about events whose actual outcomes (typically) have not yet been observed.
Examples of forecasting would be predicting weather events, forecasting sales for a particular time period or predicting the outcome of a sporting event before it is played.
Wikipedia defines Predictive Analytics as an area of statistical analysis that deals with extracting information from data and using it to predict future trends and behavior patterns.
Examples of predictive analytics would be determining customer behavior, identifying patients that are at risk for certain medical conditions or identifying fraudulent behavior.
Based on these definitions, forecasting and predictive analytics seem to be very similar…but are they? Let’s break it down.
Both forecasting and predictive analytics are concerned with predicting something in the future, something that has not yet happened. However, forecasting is more concerned with predicting future events whereas predictive analytics is concerned with predicting future trends and/or behaviors.
So, from a business perspective, forecasting would be used to determine how much of a material to buy and keep on stock based on projected sales numbers. Predictive analytics would be used to determine customer behavior like what and when are they likely to buy, how much do they spend when they do buy, and when they buy one product what else do they buy (also known as basket analysis).
Predictive analytics can be used to drive sales promotions targeting certain customers based on the information we know about their buying behavior. Likewise, the information obtained from predictive analytics can be used to influence sales projections and forecasting models.
Both, predictive analytics and forecasting, use data to achieve their purposes. But, it’s how they use that data that is much different.
In forecasting, data is used to look at past performance to determine future outcomes. For instance, how much did we sell last month or how much did we sell last year at this time of year. In predictive analytics, we are looking for new trends, things that are occurring now and in the future that will affect our future business. It is more forward looking and proactive.
So, although forecasting and predictive analytics are similar and closely related to one another, they are two distinctively different concepts. In order to be successful at either one, you have to have the right resources and tools in place to be able to extract, transform and present the data in a timely manner and in a meaningful way.
A common problem in business today is people spend much more time preparing and presenting information than they do actually determining what the data is telling them about their business. This is because they don’t have the right resources and tools in place.
At LÛCRUM we have the resources, strategies and tools to help businesses access, manage, transform and present their data in a meaningful way. If you would like to learn more about how LÛCRUM can help your business, visit our website or contact us today.
Often in the business world, things come along that drive change. Sometimes, the change could be subtle. Sometimes the change is dramatic. In a lot of cases, there are those that are early adopters, as well as those that one can count on to wait until the change is deemed mature by the industry experts. It is important also to put forth a value proposition to adopt the change; to change for change’s sake generally doesn’t help the bottom line. In some cases, this change crosses industries and technology, but sometimes the change is among clusters of business that gives one a competitive advantage over another.
Consider some of the transformations that have happened over the past few decades:
- The computer
- The internet
- Mobile technology
- Laws (SOX, etc.)
- Hybrid vehicles
- Global economics
- Social networks
Companies that were able to see these changes coming were able to prepare. Companies that didn’t see it coming were forced to adapt. It is obvious to see that being prepared is arguably the best alternative, but in many cases and for many reasons, this may not be financially, socially, or logistically possible during the early adoption period. Eventually, over time, more and more companies adapt the change into the culture or technology as it becomes more and more pervasive and valuable. Those that take the lead and the initiative generally experience growing pains, but also gain advantages of working out the kinks of emerging technology or change. Those that wait may need to face consequences for the delay but prolong the disruption to critical process for as long as possible.
So what would we say are some changes that are on the way if not already here that will help shape the next decade of business activity? One would argue that “Big Data” is a great candidate for the next major change we are beginning to feel the effects of as its existence begins to transform the business landscape.
So what is “Big Data”? According to Gartner[1] Big Data is defined as:
Big data is the term adopted by the market to describe extreme information management and processing issues which exceed the capability of traditional information technology along one or multiple dimensions to support the use of the information assets. Throughout 2010 and into 2011, big data has focused primarily on the volume issues of extremely large datasets generated from technology practices such as social media, operational technology, Internet logging and streaming sources. A wide array of hardware and software solutions has emerged to address the partial issue of volume. At this point, big data, or extreme information processing and management, is essentially a practice that presents new business opportunities.
The definition leaves the reader with a lot questions. What is “extreme information management”? What are the “hardware and software solutions” that attempt to address the issues? What are the “new business opportunities”? Let’s take a look some of these questions in more detail.
Extreme Information Management
When we look at the sheer volume or magnitude of some of the datasets that would make up a Big Data solution, it is clear the traditional processes of data management will be challenged. The normal ways of loading, storing, processing, evaluating, and analyzing this information has to change in order to reap the benefits inside the datasets. This means the normal way a technologist would write a query needs to change. The usual backup and recovery process has to be re-considered. In addition, how this “extreme” information is combined with the “traditional” information is the new conundrum businesses that are going down this path are facing. In a practical sense, a company that has a traditional data warehouse in place will be faced with the challenge of aligning existing dimensions with the new “dimensions” from the big data arena. If this challenge can be solved for an enterprise, then the competitive advantage discussed earlier can be realized because the power of leveraging changes. If a company can at least begin evaluating the contents of big data as it relates to their enterprise, they will still gain valuable insights and correlations that are eluding the competitors that will wait out the change until it is mature.
Hardware and Software Solutions
When a company is considering a big data solution, immediately the existing infrastructure stack will be impacted. There are a lot of vendors that are stepping up into the technology gap to help customers move forward with initiatives. In a lot of cases, storage and processing power will become immediate needs. Deep in the internals of big data solutions is the idea of multiple worker servers that take on distributed work to break down the processing into smaller chunks. This can be achieved with potentially low cost servers, but a lot of them depending on the scale desired. The open source community has been a leader in this arena of solutions that help address the big data problem with low cost entry into public offerings. For the technologist, this means learning new ways of addressing data access using environments like Hadoop (http://hadoop.apache.org/) or HPCC (http://hpccsystems.com/). The traditional ETL tool vendors like Pentaho (http://www.pentaho.com/) are also attempting to get in the game by extending their products to work in a big data environment. In the long run, we expect the vendors to all address “Big Data” in some form or fashion, suggesting the change is here to stay. Therefore, it would be wise to do some research in the current vendor offering or begin to experiment with some of the solution options that are available, in order to begin to reap some of the benefits of a big data solution.
New Business Opportunities
When considering what new business opportunities will be presented as a result of engaging in a Big Data environment, the potential is alluring. When dealing with datasets in the terabyte and petabyte range, the scope and makeup of the results go from specifics to generalities in rapid order. It is currently feasible to look at things in a dimensional model like perspective. It is difficult and in some cases no longer possible to calculate results as you would normally do in traditional database environments because the sheer physics have changed. But there are opportunities for businesses to integrate this new landscape into their current Business Intelligence environments. Some companies are finding ways to use sources from public web sites to private applications to drive value and competitive advantage. The government is even seeing the opportunity and critical need to get involved[2]. With this much activity related to a single discipline, we would recommend actively seeking out the opportunities in your own business environment. More than likely, your competitors already are.
What are the challenges?
Some of the challenges will be related to identifying sources, because sometimes these are external to a business and require creative thought to see the big picture and the analytical opportunities. Additional challenges will be related to bringing a technical staff up to speed on new technology and new ways of thinking related to size and scale of Big Data environments. Furthermore, there will be changes to “normal” data acquisition and storage policies. In addition to all this, there still is the integration issue. This issue can be more complex for companies that already have a mature data warehouse environment, and wish to navigate from a specific dimensional model to a less specific Big Data analysis. The bridge between the two can be daunting, physically and philosophically.
What does this mean for you?
Although Big Data is still an emerging technology and concept, there is enough momentum in the marketplace that warrants serious consideration for customers and clients. There are still significant challenges in bringing it all together in a comprehensive Business Intelligence environment. The ability for systems to collect more and more data points going forward is inevitable, and systems that can evaluate the large data sets will become more and more ingrained in the normal technical environment. The traditional systems and big data systems will become more seamless over time. The more companies can leverage the information investment on all the data points as they come available or affects their business, the more effective they will become.
If you would like to learn more about Big Data and what impact it may have in your environment or are just curious about how to approach the challenges in this new arena, we would love to help work through it with you.
More information on BIG DATA can be found online at www.lucruminc.com. Or to see how LÛCRUM can help your business with its BIG DATA needs, contact us.
[1] (http://www.gartner.com/it-glossary/big-data/),
[2] (see article here: http://www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_press_release_final_2.pdf)
A great list of big data sources is found here: http://www.zdnet.com/top-10-categories-for-big-data-sources-and-mining-technologies-7000000926/
A number of recent studies have shown that, among other things, up to 94% of spreadsheets used today contain errors.
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How happy are your customers with your service? How profitable is your business? How many new customers did your latest promotion attract? What is most important to the 20% of your customers that drive 80% of your revenue? What if you could know all this and more right now, in real time?
Information such as this might likely drive decisions as to how you would manage the future of your business. Information such as this would help you identify the most important problems facing your business, and then to solve them accordingly.
The source of information like this probably exists within your company right now, most like in the raw state known as data. Like to a vein of gold lurking underneath the grassy surface of the earth, you could be siting on top of a mountain of wealth and not even know it. That wealth is not always readily apparent, and often, like ore, requires some refinement before value can be realized. Sometimes it must be cleansed. Sometimes external elements must be added. At the end of the process, you have something whose value to the world is obvious.
Why doesn’t everyone have great information? First you just need to know what to look for. Next you need to know where to look for it. Finally you need to know what to do once you find it. Once all of this is accomplished you can ply this asset for tremendous and previously unrealized value.
Data can live in file folders, spread sheets, data bases, email messages, web sites, etc… It surrounds us. This abundant natural resource, if mined properly, refined thoughtfully, and shaped intentionally can yield information and knowledge whose value is literally as good as gold.
This information could be the difference from having an effective service recovery problem that addresses customer concerns in real time or having countless unhappy customers telling 3,000 of their closest friends on the web how you failed to deliver. Information and action could make the difference.
This information could be the difference between pulling the plug on that seemingly unpopular product line, or realizing that the unprofitable product actually helps to sell the profitable one because it is bought in tandem. Information and action could make the difference.
This information could be the difference between guessing as to the financial health of your business or knowing with certainty if some cancer exists within your business – if not caught early will result in the death of your firm. Information and action could make the difference.
Good information, and what you choose to do with it, can make all the difference in the world.
The New York Times recently ran an excellent article by John Markoff about the changing concept of individual privacy in the digital age. The article discusses some of the implications associated with being increasingly connected. GPS enabled devices, online activity, social networks, credit card purchases, and other technologies can paint a vivid profile of an individual, which could be used by numerous sources for activites both good and bad.
How could such data be used for good? Suppose a company possessed information about where you are, what you are doing, and why; they could offer you real time incentives to purchase specific products. It would be analogous to virtual haggling to get consumers to behave a certain way. Need a pair of dress shoes? Are you at the mall? You wear a size 11 right? Well suppose a retailer within the mall knew you were there looking for a size 11 dress shoe, which they just so happen to have an abundance of in stock. They could text you a message stating that for the next 3 hours you could redeem the text on a new set of black loafers – size 11. Not only that, they also know that your spouse has a birthday coming up, and will offer you buy one get one 1/2 off to incent you to purchase more footwear. They know the correct size, and have the ability to make suggestions based on past purchases and the purchases of similar consumers.
Now suppose that this offer is passed up repeatedly by consumers within a period of time. Just like that, the deal could be modified until the desired consumer behavior occurs. Hyperefficient capitalism at its best.
How could such data be used for not so good? Well, that retailer or perhaps the credit card company, may note that you are buying special shoes designed for people with circulatory issues as well as special clothing to help improve circulation in extremities. They may also note that you are purchasing sugar free candy at the counter, and that you bought a sugar-free latte. Later, their video might capture footage of you sitting on a bench eating a cookie and drinking juice you bought in the store. Now suppose an insurance company is concerned about the cost of covering people with diabetes, and wanted to obtain data regarding consumers of specific items that those with diabetes might purchase. They could follow your activities thorough data purchased from the retailer and make judgements about your risk profile. This data could then be used to deny coverage to consumers. Hyperefficient capitalism at its worst.
Both of these scenarios are hypothetical in nature and admittedly oversimplified. One involves the use of data to help a consumer get something they desire. The other involves the use of similar data to deny a consumer from something they desire. Both involve the elimination of privacy as more and more data is collected about us – sometimes knowingly and sometimes not.
Still, it seems that people overall are not particularly concerned with the collection of personal data. The attitude toward the loss of privacy in exchange for convenience is overwhelmingly laissez faire. As Markoff ponders, in an age of Google, iphones, GPS, and Facebook, has privacy “become an anomaly?”
The question becomes what is your company doing with its data? For most, the reality of today is likely nothing, or at best very little. For all of the hype surrounding the potential use of data, much of this valuable information sits fallow within the servers, computers, and files of firms. The big ideas are out there, and now it is a question of who will capitalize on them – good, bad, or otherwise.
Is your company formally gathering, processing and utilizing data to influence consumer behavior? Could you? Are you adequately protecting the privacy of your Clients? Should you be? Are individuals within your firm potentially accessing sensitive information for their own interests? Is your competition doing a better job of mining the collective intelligence provided by data than you are?
The reality of today is that you have an amazing opportunity to impact the lives of those whom you serve through data. How you do so is largely up to you. For the record, I am a huge fan of size 10 Adidas Gazelles, and I would love a red pair. The next time I am near your store, text me and let me know if you have a great deal for me.
You’re Leaving a Digital Trail. What About Privacy? – NYTimes.com
LUCRUM does Business Intelligence
Well, what does that mean? What do we provide for our clients? What makes LUCRUM different that other companies who “do BI”? Why should someone call LUCRUM in the first place? What value does LUCRUM focus on? If I was on an elevator and someone asked what we do for BI, what would I say?
Well, depending upon the elevator ride…here is one paragraph for every three floors of a ride about what we at LUCRUM do in the business intelligence space.
We have a proven track record of creating and providing value to our clients because we are highly skilled in both the art of aligning senior leadership around a game-changing passionate vision – a vision that takes their organization to the next level – and the science of synthesizing systems and data from disparate data sources into a focused and leveraged answer to the organization’s most important questions.
We never stop asking how and why. We find that the true questions are often 5 levels deep. We operate at this level – at the most intimate levels, where answers cause real action that changes the course of the organization. And then we never stop asking where. We unhide the data throughout the organization by liberating, assembling and bringing it together in the right manner, at the right time, delivering it to the right people.
We strive to hide complexities and present the answers to those truly valuable questions in a way that enables executives make the most use of their time by pinpointing the problem (or success) quickly. This early warning gives them the competitive edge and allows them to adjust strategy and tactics before their competitors have a chance to react.
In essence – we deliver value in the form of time to our clients. In action this translates as an increase in the critical response time that our clients leverage to act correctly before their competitors, who then are left in the position of reaction.
My closing statements would be:
- Business Intelligence is 100% art and 100% science.
- Truth is never at the surface, its usually pretty deep – but worth the trip.
- Simplicity implies that complexity and intricacy are under control.
- Time is the most precious non-renewable resource on the planet!
Putting all this together – Your organization has very expensive data sitting around decaying as time goes by. What are the most important questions that when answered sheds light on actions that reduce risk, promote change or brings about exponential growth? Align these at the highest levels and don’t rest until you unhide the right data, connect the information and present to the right person at the right time!
BI – Business Intelligence or Bringing Innovation, Better Information, Best Ideas, Big Imaginations, Bold Image… Whatever it means to you, will either help you or your competition.
You decide!
~ Scott Felten
- LÛCRUM is an information, intelligence and analytics consulting firm comprised of business and technology professionals focused on making data meaningful.
