Sales Force Marketing For Big Data Solutions

How to Grow a Business

How to Grow a Business: When Big Companies Were Small [Infographic]

 

 

Even the biggest multi-billion dollar conglomerate started off as a small business.  After studying some of the most dominant brands, it’s clear there was one common denominator that they share when growing their business — having a clear vision.

A clear vision of what you want to accomplish is one of the factors that will ultimately help grow your business from a small startup to big time player. Want to know how to grow your business? See how global brands such as Apple, Google, and Facebook did it.

Apple has brought about one of the most monumental changes with its innovative mobile devices and impeccable designs, which all started with Steve Job’s vision of allowing the individual and aesthetics to be the center of the computing universe, not the mainframe. Google toppled all search engines in the industry based on their ability to scale and make the web free for everyone. Facebook completely redefines how we connect with friends and brands and this success is attributed to their persistence in growing during pivotal points rather than selling it off.

While it is hard to recall sometimes, all these brands had their defining years of growth and they all kept to their vision.  Do you want to learn how to grow a business? Check out how these global enterprises got their starts!

Growing a business? Download our free ebook to learn more about the Top 10 features you need in a CRM.

note: click on the image to see a larger version

Using Big Data to Make Better Pricing Decisions

Taking advantage of the flood of information readily available from customer interactions enables firms to price properly– and reap the rewards.

It’s difficult to overstate the value of acquiring pricing right. Usually, a 1 percent price boost translates into an 8.7 percent boost in operating revenues (presuming no loss of quantity, certainly). Yet we approximate that up to 30 percent of the thousands of rates choices firms make each year fail to supply the very best rate. That’s a bunch of shed income. And it’s specifically unpleasant taking into consideration that the flood of data now offered supplies business with a chance to make dramatically far better pricing decisions. For those able to bring order to huge information’s complexity, the value is considerable.

We’re not suggesting it’s easy: the number of consumer touchpoints keeps exploding as digitization energies growing multichannel intricacy. Yet price factors have to keep up. Without revealing and acting on the chances large information presents, many business are leaving millions of dollars of revenue on the table. The key to boosting revenue margins is to use huge information to find the most effective rate at the item– not group– degree, instead of drown in the numbers flood.

Too Large to Be successful
For each item, firms ought to be able to find the superior price that a customer is willing to pay. Preferably, they would certainly factor in very specific ideas that would certainly influence the price– the cost of the next-best competitive product versus the worth of the product to the consumer, for instance– then come to the best rate. Without a doubt, for a firm with a handful of items, this kind of rates strategy is uncomplicated.

pricing strategiesIt’s more bothersome when item numbers balloon. Concerning 75 percent of a typical firm’s earnings comes from its basic products, which frequently number in the thousands. Lengthy, hands-on methods for setting costs make it essentially difficult to view the rates designs that can open worth. It’s simply as well overwhelming for huge business to obtain granular and take care of the complexity of these prices variables, which alter regularly, for thousands of items. At its core, this is a huge information problem.

Several marketers end up simply burying their heads in the sand. They establish prices based upon simplistic factors such as the expense to generate the item, typical margins, costs for similar items, volume markdowns and more. They fall back on aged methods to take care of the items as they always have or mention “market prices” as a justification for not attacking the concerns. Possibly worst of all, they rely on “attempted and checked” historical techniques, such as a global 10 percent price walk on every little thing.

“Exactly what occurred in technique then was that each year we had actually price increases based upon scale and quantity, yet not based on science,” states Roger Britschgi, head of offers operations at Linde Gases. “Our individuals merely really did not believe it was feasible to do it any other way. And, rather truthfully, our people were not well prepared to persuade our consumers of the have to enhance rates.”.

Four Steps to Turn Data into Revenues.
The trick to far better prices is knowing fully the data now at a firm’s disposal. It requires not zooming out yet zooming in. As Tom O’Brien, team vice president and basic manager for marketing and sales at Sasol, mentioned of this method, “The [offers] groups recognized their rates, they might have understood their volumes, yet this was something much more: incredibly granular information, essentially from each and every statement, by product, by client, by packaging.”.

In fact, a few of the most stimulating examples of utilizing large data in a B2B context actually transcend pricing and touch on various other elements of a business’s industrial engine. As an example, “dynamic discount rating” gives price guidance at the level of specific offers, decision-escalation points, rewards, performance scoring, and a lot more, based upon a collection of similar win/loss offers. Utilizing smaller sized, relevant discount examples is important, as the aspects connected to any sort of one deal will differ, leaving an overarching collection of deals worthless as a benchmark. We’ve viewed this applied in the modern technology industry with wonderful success– generating increases of four to eight percent factors in return on offers (versus same-company control groups).

To obtain sufficiently granular, business need to do four points.

Hear the data. Establishing the most effective costs is not a data obstacle (companies typically already sit on a bonanza of information); it’s an evaluation difficulty. The most effective B2C firms know how you can translate and act upon the wide range of information they have, but B2B companies have the tendency to handle data as opposed to utilize it to drive decisions. Great analytics could aid business identify how elements that are often neglected– such as the wider financial situation, item choices and sales-representative agreements– expose what drives rates for every customer section and product.

Automate. It’s too pricey and lengthy to examine thousands of items manually. Automated devices can recognize narrow sectors, identify exactly what drives worth apiece and match that with historic transactional data. This enables business to establish prices for collections of products and sectors based on data. Automation likewise makes it much easier to reproduce and fine-tune analyses so it’s not needed to start from scratch every single time.

Construct skills and confidence. Carrying out new prices is as much a communications difficulty as a functional one. Effective companies overinvest in thoughtful change programs to assist their offers pressures know and accept new rates techniques. Business need to function closely with offers reps to detail the reasons for the price suggestions and how the system works to ensure that they rely on the costs sufficient to sell them to their customers. Similarly essential is establishing a clear collection of communications to offer a reasoning for the prices in order to highlight value, then modifying those disagreements to the customer.

Demanding arrangement training is also essential for offering sales representatives the self-reliance and devices to make convincing arguments when speaking to customers. The most effective leaders accompany sales representatives to the most challenging customers and focus on acquiring quick wins so that sales reps develop the self-reliance to take on the brand-new rates strategy. “It was vital to show that management was behind this new technique,” mentions Robert Krieger, managing supervisor of PanGas AG. “And we did this by joining brows through to challenging consumers. We were able to not just assist our offers representatives however likewise demonstrate how the argumentation functioned.”.

Definitely manage efficiency. To improve performance administration, firms need to sustain the sales force with useful targets. The greatest influence originates from guaranteeing that the cutting edge has a straightforward look at of earnings by customer and that the offers and advertising and marketing company has the ideal logical skills to recognize and make the most of the possibility. The offers pressure additionally should be empowered to change rates itself rather than relying upon a centralized group. This requires a level of imagination in designing a customer-specific rate strategy, along with an entrepreneurial way of thinking. Motivations might additionally have to be changed together with pricing policies and efficiency dimensions.

We’ve seen business in industries as diverse as software program, chemicals, building materials and telecoms accomplish impressive outcomes by utilizing large information to notify far better pricing decisions. All had substantial varieties of SKUs and purchases, in addition to a fragmented profile of clients; all saw a profit-margin lift of in between 3 and 8 percent from establishing rates at a lot more granular product levels. In one instance, a European building-materials firm set prices that boosted margins by around 20 percent for selected items. To get the cost right, companies need to benefit from big data and spend enough resources in assisting their offers reps– or they may discover themselves paying the higher rate of lost revenues.

Utilizing Big Information to Make A lot better Rates Choices

Taking advantage of the flood of data readily available from customer interactions permits firms to rate properly– and experience the benefits.

It’s tough to overstate the relevance of obtaining pricing right. On average, a 1 percent cost increase equates into an 8.7 percent boost in running revenues (presuming no loss of volume, naturally). Yet we estimate that up to 30 percent of the countless pricing choices companies make each year fall short to deliver the most effective rate. That’s a lot of shed revenue. And it’s particularly distressing thinking about that the flood of data now available provides companies with a chance to make substantially much better pricing decisions. For those able to bring order to huge information’s intricacy, the value is significant.

We’re not proposing it’s simple: the variety of client touchpoints keepings exploding as digitization energies growing multichannel intricacy. Yet price points have to keep pace. Without uncovering and acting upon the possibilities big information presents, several business are leaving millions of dollars of profit on the table. The trick to raising revenue margins is to use big information to locate the most effective rate at the item– not classification– level, rather than sink in the numbers flood.

Also Big to Prosper
For every single product, companies need to have the ability to locate the optimum rate that a consumer is willing to pay. Ideally, they ‘d consider extremely particular understandings that would certainly influence the rate– the price of the next-best competitive item vs. the worth of the product to the consumer, for example– and afterwards get to the very best cost. Undoubtedly, for a firm with a handful of products, this kind of prices method is uncomplicated.

pricing strategiesIt’s more problematic when item numbers balloon. About 75 percent of a typical firm’s earnings originates from its common products, which commonly number in the many thousands. Lengthy, hands-on practices for establishing costs make it basically difficult to view the prices patterns that could unlock worth. It’s just too overwhelming for big companies to obtain granular and take care of the complexity of these pricing variables, which transform regularly, for thousands of items. At its core, this is a huge information concern.

Many online marketers wind up just burying their heads in the sand. They establish prices based on simplified aspects such as the expense to produce the item, conventional margins, prices for comparable items, volume price cuts and so forth. They draw on aged practices to take care of the products as they always have or mention “market prices” as a justification for not assaulting the concerns. Probably worst of all, they rely upon “tried and checked” historical techniques, such as an universal 10 percent price hike on everything.

“Just what happened in practice then was that each year we had rate increases based upon scale and volume, however not based on science,” says Roger Britschgi, head of offers operations at Linde Gases. “Our people merely really did not think it was feasible to do it differently. And, quite honestly, our people were not well prepared to encourage our clients of the should enhance rates.”.

Four Tips to Turn Information into Profits.
The secret to far better pricing is recognizing totally the information now at a firm’s disposal. It needs not zooming out but focusing. As Tom O’Brien, group vice president and basic manager for advertising and offers at Sasol, mentioned of this strategy, “The [offers] teams knew their pricing, they may have recognized their volumes, however this was something much more: incredibly granular data, essentially from each and every invoice, by item, by consumer, by product packaging.”.

In fact, a few of the most amazing examples of using large information in a B2B context actually transcend rates and touch on other elements of a business’s commercial engine. For example, “dynamic discount rating” supplies rate guidance at the degree of individual discounts, decision-escalation factors, rewards, efficiency scoring, and more, based on a collection of comparable win/loss discounts. Utilizing smaller sized, pertinent deal samples is essential, as the aspects connected to any type of one offer will differ, making an overarching set of deals useless as a standard. We’ve seen this used in the innovation sector with terrific success– producing boosts of 4 to eight percent factors in return on offers (versus same-company control groups).

To get sufficiently granular, companies have to do four things.

Pay attention to the data. Establishing the most effective costs is not a data difficulty (firms typically currently rest on a treasure of data); it’s an analysis obstacle. The best B2C firms recognize the best ways to translate and act upon the wealth of information they have, however B2B firms often handle information instead of use it to drive decisions. Excellent analytics can aid firms determine just how factors that are frequently neglected– such as the broader economic scenario, product choices and sales-representative arrangements– reveal what drives prices for each and every customer segment and product.

Automate. It’s as well costly and taxing to evaluate thousands of items by hand. Automated systems can recognize narrow sectors, identify just what drives worth apiece and match that with historical transactional information. This permits companies to establish prices for collections of products and segments based on information. Automation also makes it much easier to reproduce and tweak evaluations so it’s not necessary to start from scratch every time.

Build skills and confidence. Executing new rates is as a lot an interactions difficulty as a functional one. Effective business overinvest in considerate modification programs to help their sales forces recognize and welcome brand-new rates strategies. Companies should function very closely with sales representatives to explain the factors for the rate suggestions and just how the device functions so that they rely on the costs good enough to sell them to their consumers. Similarly vital is creating a clear collection of communications to supply a rationale for the rates in order to highlight value, and afterwards modifying those arguments to the consumer.

Demanding negotiation training is additionally essential for offering offers representatives the self-confidence and tools to make persuading disagreements when speaking with customers. The best leaders go along with sales reps to the most tough members and focus on getting fast success to make sure that sales reps establish the self-reliance to adopt the brand-new prices strategy. “It was essential to show that management lagged this new method,” says Robert Krieger, taking care of supervisor of PanGas AG. “And we did this by signing up with brows through to challenging clients. We had the ability to not simply help our sales representatives but likewise show how the argumentation functioned.”.

Actively handle performance. To boost performance management, business should sustain the offers force with useful targets. The greatest effect originates from guaranteeing that the front line has a clear perspective of success by consumer which the offers and advertising company has the right analytical capabilities to acknowledge and capitalize on the possibility. The offers force also has to be equipped to change prices itself rather than relying upon a central group. This requires a degree of creativity in designing a customer-specific cost method, in addition to an entrepreneurial way of thinking. Incentives could additionally should be altered along with rates policies and performance dimensions.

We’ve seen firms in industries as varied as software, chemicals, building products and telecommunications accomplish excellent results using large data to notify better rates choices. All had massive varieties of SKUs and purchases, in addition to a fragmented profile of consumers; all viewed a profit-margin lift of between 3 and 8 percent from establishing prices at a lot more granular product levels. In one instance, a European building-materials firm set costs that increased margins by around 20 percent for selected items. To get the price right, business need to capitalize on large data and invest more than enough sources in sustaining their offers representatives– or they may find themselves paying the higher price of shed profits.

Using Big Data to Make Much better Prices Decisions

Utilizing the flood of information offered from client communications permits firms to price suitably– and gain the incentives.

It’s difficult to overstate the importance of obtaining prices right. On average, a 1 percent price increase equates into an 8.7 percent increase in operating revenues (assuming no loss of volume, certainly). Yet we approximate that as much as 30 percent of the countless pricing choices firms make yearly fall short to deliver the most effective rate. That’s a lot of shed income. And it’s specifically uncomfortable taking into consideration that the flood of data now offered offers business with a chance to make considerably much better prices choices. For those able to introduce order to big information’s complexity, the value is considerable.

We’re not recommending it’s very easy: the number of customer touchpoints keepings exploding as digitization fuels increasing multichannel complexity. Yet rate factors should keep pace. Without revealing and acting on the possibilities large information presents, numerous companies are leaving millions of bucks of earnings on the table. The secret to enhancing earnings margins is to utilize big information to discover the very best price at the product– not group– level, as opposed to drown in the numbers flood.

As well Huge to Succeed
For every product, firms should manage to find the optimal rate that a consumer is willing to pay. Ideally, they ‘d factor in very particular insights that would certainly affect the cost– the expense of the next-best affordable item against the worth of the product to the customer, for instance– then get to the best rate. Without a doubt, for a business with a handful of items, this sort of prices technique is uncomplicated.

pricing strategiesIt’s even more problematic when product numbers balloon. About 75 percent of a common company’s profits originates from its standard items, which often number in the many thousands. Time-consuming, hand-operated methods for establishing prices make it basically difficult to view the prices designs that could unlock value. It’s simply too frustrating for huge firms to get granular and handle the complexity of these prices variables, which alter continuously, for hundreds of products. At its core, this is a big information concern.

Many marketing experts wind up merely burying their heads in the sand. They develop rates based on simplistic elements such as the price to generate the product, conventional margins, rates for comparable items, quantity discount rates and so forth. They draw on aged techniques to manage the products as they always have or mention “market prices” as an excuse for not assaulting the issues. Perhaps worst of all, they count on “attempted and examined” historical methods, such as a global 10 percent cost trip on everything.

“Exactly what happened in method then was that yearly we had actually rate boosts based upon scale and volume, yet not based upon science,” says Roger Britschgi, head of offers procedures at Linde Gases. “Our individuals merely didn’t believe it was possible to do it otherwise. And, very frankly, our individuals were not well ready to convince our customers of the should raise costs.”.

Four Pointers to Turn Data into Profits.
The key to better pricing is understanding completely the data now at a business’s disposal. It needs not zooming out yet focusing. As Tom O’Brien, team vice head of state and general supervisor for marketing and offers at Sasol, mentioned of this approach, “The [offers] teams recognized their pricing, they may have recognized their volumes, yet this was something much more: very granular information, actually from each and every statement, by item, by consumer, by product packaging.”.

In fact, some of the most exciting instances of utilizing big data in a B2B context really transcend rates and discuss other aspects of a business’s commercial engine. For example, “powerful offer rating” offers price advice at the level of individual offers, decision-escalation factors, motivations, efficiency rating, and a lot more, based upon a collection of comparable win/loss bargains. Utilizing smaller sized, appropriate discount samples is important, as the elements linked to any kind of one discount will certainly differ, leaving an overarching collection of deals ineffective as a benchmark. We’ve seen this used in the innovation industry with excellent success– generating rises of four to eight portion factors in return on sales (versus same-company control groups).

To get completely granular, firms need to do 4 things.

Pay attention to the data. Establishing the best costs is not an information obstacle (companies normally already rest on a treasure trove of information); it’s an analysis difficulty. The most effective B2C firms recognize the best ways to interpret and act on the wealth of information they have, but B2B business have the tendency to take care of data instead of utilize it to drive choices. Good analytics could help companies identify just how aspects that are commonly ignored– such as the more comprehensive economic circumstance, product choices and sales-representative settlements– reveal what drives prices for each and every client section and item.

Automate. It’s too costly and lengthy to examine thousands of items manually. Automated devices can identify slim sections, determine what drives value for each one and match that with historic transactional information. This permits firms to establish prices for clusters of items and sections based upon data. Automation also makes it much easier to duplicate and tweak analyses so it’s not essential to go back to square one every single time.

Build skills and confidence. Implementing new prices is as considerably an interactions difficulty as a functional one. Successful firms overinvest in considerate change programs to help their offers pressures recognize and welcome brand-new pricing techniques. Firms need to function closely with offers representatives to explain the reasons for the rate recommendations and exactly how the system works to make sure that they trust the prices good enough to market them to their consumers. Equally essential is establishing a clear set of interactions to provide a purpose for the costs in order to highlight value, then customizing those debates to the customer.

Demanding settlement training is also crucial for providing sales reps the self-confidence and devices to make prodding disagreements when speaking to customers. The very best leaders accompany sales reps to the most hard clients and concentrate on obtaining quick success to make sure that sales reps create the self-reliance to embrace the brand-new pricing method. “It was critical to show that management was behind this brand-new approach,” claims Robert Krieger, handling supervisor of PanGas AG. “And we did this by joining check outs to challenging consumers. We were able to not simply help our sales representatives yet additionally show how the argumentation functioned.”.

Definitely take care of efficiency. To enhance efficiency management, companies have to assist the sales pressure with beneficial targets. The best effect originates from guaranteeing that the cutting edge has a straightforward look at of profitability by customer and that the offers and advertising and marketing organization has the appropriate logical abilities to identify and benefit from the opportunity. The sales force additionally should be encouraged to change prices itself instead of depending on a centralized team. This requires a level of ingenuity in designing a customer-specific price approach, and also a business mind-set. Incentives may likewise need to be altered alongside pricing plans and performance measurements.

We have actually seen business in sectors as varied as software application, chemicals, construction products and telecoms accomplish remarkable outcomes using large information to notify better prices decisions. All had enormous varieties of SKUs and deals, as well as a fragmented portfolio of clients; all viewed a profit-margin lift of between 3 and 8 percent from establishing costs at a lot more granular product levels. In one instance, a European building-materials firm set prices that increased margins by as much as 20 percent for picked items. To obtain the rate right, business ought to capitalize on huge data and spend enough resources in assisting their offers representatives– or they may locate themselves paying the higher rate of lost profits.

Using Big Data to Make Much better Rates Decisions

Harnessing the flood of information available from consumer communications permits business to price appropriately– and gain the rewards.

It’s hard to overemphasize the significance of getting prices right. On average, a 1 percent cost boost equates into an 8.7 percent boost in running earnings (assuming no loss of volume, obviously). Yet we approximate that as much as 30 percent of the thousands of pricing choices companies make every year fail to supply the most effective price. That’s a great deal of lost income. And it’s particularly troubling thinking about that the flood of data now offered supplies firms with a possibility to make considerably better pricing choices. For those able to bring order to big information’s complexity, the worth is substantial.

We’re not proposing it’s simple: the number of consumer touchpoints keepings exploding as digitization gases increasing multichannel complexity. Yet rate points need to keep pace. Without revealing and acting on the opportunities large information presents, lots of business are leaving countless bucks of earnings on the table. The technique to raising profit margins is to use huge data to discover the very best cost at the product– not group– level, as opposed to drown in the numbers flood.

Too Large to Be successful
For every product, firms ought to manage to find the ideal cost that a consumer is willing to pay. Ideally, they ‘d factor in very specific understandings that would certainly influence the price– the expense of the next-best affordable item against the worth of the product to the consumer, for instance– then find the best rate. Indeed, for a business with a handful of items, this type of pricing technique is uncomplicated.

prices strategiesIt’s even more bothersome when item numbers balloon. Concerning 75 percent of a typical business’s revenue originates from its basic products, which commonly number in the many thousands. Lengthy, manual methods for setting costs make it essentially difficult to see the prices patterns that can open worth. It’s merely also frustrating for big firms to get granular and take care of the intricacy of these rates variables, which transform frequently, for thousands of items. At its core, this is a huge information issue.

Many online marketers wind up just burying their heads in the sand. They create rates based upon simplified aspects such as the price to produce the item, typical margins, costs for similar items, quantity markdowns and so on. They fall back on old practices to manage the products as they consistently have or cite “market prices” as a justification for not assaulting the concerns. Probably worst of all, they rely upon “tried and checked” historical methods, such as an universal 10 percent price trek on everything.

“What took place in practice then was that every year we had cost rises based upon scale and volume, yet not based on science,” claims Roger Britschgi, head of offers procedures at Linde Gases. “Our individuals merely really did not assume it was feasible to do it any other way. And, very truthfully, our people were not well prepared to persuade our customers of the have to raise prices.”.

Four Pointers to Turn Data into Earnings.
The key to much better pricing is comprehending fully the data now at a firm’s disposal. It calls for not zooming out however zooming in. As Tom O’Brien, team vice president and basic supervisor for advertising and marketing and offers at Sasol, claimed of this approach, “The [sales] teams knew their prices, they could have understood their quantities, however this was something much more: remarkably granular information, literally from each and every statement, by item, by client, by packaging.”.

Actually, a few of the most exciting instances of utilizing large information in a B2B context really transcend rates and discuss other facets of a business’s commercial engine. For instance, “powerful discount rating” offers price guidance at the level of specific bargains, decision-escalation points, rewards, efficiency rating, and a lot more, based on a set of comparable win/loss bargains. Using smaller sized, appropriate deal examples is crucial, as the aspects linked to any type of one offer will certainly vary, rendering an overarching collection of bargains pointless as a benchmark. We’ve viewed this applied in the technology industry with terrific success– generating boosts of four to eight portion factors in return on sales (versus same-company control groups).

To obtain completely granular, firms should do four factors.

Pay attention to the information. Setting the best costs is not a data challenge (companies typically currently sit on a treasure of information); it’s an evaluation difficulty. The very best B2C companies recognize how to translate and act on the wide range of data they have, however B2B companies often handle data as opposed to utilize it to drive choices. Great analytics could aid business identify exactly how elements that are frequently ignored– such as the more comprehensive financial situation, product choices and sales-representative arrangements– reveal just what drives costs for each client sector and item.

Automate. It’s as well expensive and taxing to examine countless items manually. Automated systems could recognize slim sections, determine what drives worth apiece and match that with historical transactional information. This enables companies to establish rates for collections of products and sectors based on information. Automation additionally makes it a lot easier to duplicate and modify analyses so it’s not needed to start from scratch every single time.

Build skills and confidence. Carrying out new rates is as considerably an interactions challenge as a functional one. Effective firms overinvest in thoughtful change programs to help their sales forces understand and embrace new rates techniques. Companies should work carefully with sales representatives to explain the factors for the cost suggestions and how the device works so that they rely on the rates good enough to market them to their clients. Similarly vital is creating a clear collection of communications to offer a purpose for the prices in order to highlight worth, and then tailoring those arguments to the customer.

Demanding arrangement training is additionally critical for giving offers representatives the self-reliance and tools to make prodding disagreements when talking with members. The best leaders accompany offers reps to the most tough clients and concentrate on obtaining quick success to make sure that offers reps establish the confidence to adopt the brand-new prices approach. “It was critical to show that leadership was behind this new strategy,” says Robert Krieger, handling supervisor of PanGas AG. “And we did this by signing up with brows through to hard consumers. We were able to not simply help our offers representatives yet likewise show how the argumentation functioned.”.

Actively take care of performance. To enhance performance management, companies should sustain the sales force with beneficial targets. The greatest impact originates from guaranteeing that the cutting edge has a clear view of productivity by customer which the offers and advertising and marketing organization has the ideal logical skills to recognize and make use of the possibility. The sales pressure also should be empowered to change rates itself as opposed to relying upon a centralized group. This requires a degree of creativity in designing a customer-specific rate strategy, as well as a business way of thinking. Rewards could additionally have to be transformed together with prices plans and efficiency measurements.

We have actually seen business in sectors as unique as software application, chemicals, construction products and telecommunications obtain remarkable results by utilizing big information to inform better rates decisions. All had substantial varieties of SKUs and purchases, along with a fragmented profile of clients; all saw a profit-margin lift of between 3 and 8 percent from establishing prices at far more granular product degrees. In one instance, a European building-materials firm established rates that boosted margins by around 20 percent for chosen items. To obtain the cost right, companies should capitalize on large data and spend sufficient sources in sustaining their sales representatives– or they may locate themselves paying the high cost of shed profits.

Using Big Data to Make A lot better Pricing Choices

Utilizing the flood of data readily available from client communications permits firms to cost suitably– and gain the benefits.

It’s hard to overstate the significance of getting pricing right. On average, a 1 percent rate boost translates into an 8.7 percent rise in running profits (presuming no loss of quantity, naturally). Yet we approximate that up to 30 percent of the countless prices choices firms make annually fail to deliver the best cost. That’s a lot of shed revenue. And it’s specifically troubling considering that the flood of data now offered offers companies with a possibility to make considerably far better pricing choices. For those able to bring order to big data’s complexity, the worth is sizable.

We’re not suggesting it’s easy: the number of consumer touchpoints keepings exploding as digitization energies growing multichannel complexity. Yet rate points need to keep up. Without uncovering and acting on the opportunities big information presents, numerous business are leaving countless bucks of revenue on the table. The technique to raising earnings margins is to harness large data to locate the most effective price at the item– not category– level, as opposed to drown in the numbers flood.

As well Big to Prosper
For every product, firms need to be able to find the superior cost that a consumer is willing to pay. Essentially, they ‘d factor in extremely specific ideas that would influence the rate– the cost of the next-best competitive item vs. the value of the item to the client, as an example– and then find the best rate. Indeed, for a company with a handful of products, this sort of prices technique is uncomplicated.

pricing strategiesIt’s even more problematic when item numbers balloon. Concerning 75 percent of a common business’s revenue comes from its common items, which commonly number in the many thousands. Taxing, manual methods for establishing rates make it virtually difficult to see the pricing designs that could unlock value. It’s just too frustrating for huge companies to obtain granular and manage the complexity of these prices variables, which change regularly, for hundreds of products. At its core, this is a huge information concern.

Numerous online marketers wind up just burying their heads in the sand. They create costs based upon simple factors such as the expense to produce the item, conventional margins, prices for comparable items, volume promos and more. They fall back on old techniques to handle the items as they always have or cite “market prices” as a reason for not assaulting the concerns. Possibly worst of all, they depend on “tried and tested” historic techniques, such as an universal 10 percent price trip on every little thing.

“Just what occurred in method then was that each year we had actually cost increases based upon scale and volume, yet not based on science,” says Roger Britschgi, head of offers procedures at Linde Gases. “Our individuals merely didn’t think it was possible to do it any other way. And, quite truthfully, our people were not well ready to encourage our customers of the should enhance costs.”.

Four Pointers to Turn Data into Earnings.
The secret to far better pricing is understanding totally the data now at a company’s disposal. It calls for not zooming out but zooming in. As Tom O’Brien, group vice president and basic manager for marketing and offers at Sasol, claimed of this approach, “The [sales] teams understood their prices, they might have understood their volumes, yet this was something more: exceptionally granular information, actually from each and every invoice, by product, by customer, by product packaging.”.

In fact, several of the most stimulating examples of utilizing big data in a B2B context actually transcend pricing and touch on other elements of a company’s commercial engine. For instance, “dynamic discount rating” supplies rate assistance at the level of specific discounts, decision-escalation factors, incentives, efficiency scoring, and more, based upon a collection of similar win/loss bargains. Making use of smaller sized, appropriate bargain examples is necessary, as the factors tied to any one discount will vary, rendering an overarching set of discounts useless as a standard. We’ve viewed this applied in the technology sector with wonderful success– yielding increases of four to eight percent points in return on offers (versus same-company control teams).

To obtain sufficiently granular, business should do four things.

Listen to the data. Setting the most effective costs is not a data obstacle (business generally currently rest on a treasure of data); it’s an evaluation difficulty. The very best B2C business recognize the best ways to translate and act on the wide range of information they have, yet B2B business often manage data instead of use it to drive decisions. Excellent analytics can assist business recognize how factors that are typically overlooked– such as the broader financial scenario, item choices and sales-representative settlements– reveal what drives prices for each and every consumer segment and product.

Automate. It’s as well pricey and taxing to evaluate hundreds of products by hand. Automated systems can recognize slim sectors, determine exactly what drives value for each one and match that with historic transactional data. This enables firms to establish prices for clusters of products and sections based upon data. Automation also makes it much easier to duplicate and modify evaluations so it’s not required to go back to square one each time.

Build abilities and confidence. Executing brand-new rates is as considerably an interactions challenge as an operational one. Effective business overinvest in thoughtful change programs to assist their offers forces understand and accept new prices strategies. Business should work closely with sales reps to discuss the factors for the cost suggestions and exactly how the device functions to ensure that they rely on the rates sufficient to offer them to their customers. Similarly important is establishing a clear collection of interactions to offer a reasoning for the prices in order to highlight worth, and then customizing those debates to the consumer.

Intensive negotiation training is additionally important for providing offers representatives the self-reliance and tools to make convincing debates when talking with members. The best leaders accompany sales representatives to the most challenging customers and concentrate on obtaining fast success so that offers representatives create the self-confidence to embrace the brand-new prices technique. “It was important to show that leadership was behind this new strategy,” mentions Robert Krieger, handling director of PanGas AG. “And we did this by signing up with brows through to tough consumers. We managed to not simply aid our sales reps however additionally show how the argumentation worked.”.

Definitely take care of performance. To enhance performance administration, companies should sustain the offers pressure with beneficial targets. The best influence originates from making sure that the front line has a clear see of profitability by client and that the offers and marketing company has the right analytical abilities to recognize and make the most of the possibility. The offers force also has to be encouraged to readjust costs itself instead of depending on a centralized team. This calls for a degree of creativity in creating a customer-specific rate method, as well as an entrepreneurial way of thinking. Rewards might additionally have to be altered along with pricing plans and efficiency dimensions.

We have actually viewed firms in industries as diverse as software program, chemicals, construction products and telecommunications accomplish outstanding outcomes by utilizing huge information to educate much better prices decisions. All had massive numbers of SKUs and deals, as well as a fragmented collection of customers; all saw a profit-margin lift of in between 3 and 8 percent from setting prices at a lot more granular item levels. In one case, a European building-materials firm set costs that boosted margins by as much as 20 percent for chosen items. To obtain the cost right, companies ought to take advantage of big data and spend adequate resources in supporting their offers reps– or they may discover themselves paying the high cost of lost earnings.

Utilizing Big Data to Make A lot better Prices Choices

Using the flood of data available from client interactions permits firms to cost suitably– and reap the benefits.

It’s hard to overstate the importance of acquiring prices right. On average, a 1 percent rate boost equates into an 8.7 percent boost in running profits (presuming no loss of volume, of course). Yet we determine that as much as 30 percent of the hundreds of prices decisions firms make annually fail to deliver the most effective price. That’s a bunch of lost earnings. And it’s particularly uncomfortable considering that the flood of data now readily available gives firms with an opportunity to make dramatically much better rates decisions. For those able to bring order to large information’s complexity, the worth is considerable.

We’re not recommending it’s very easy: the variety of consumer touchpoints keepings exploding as digitization gases growing multichannel complexity. Yet price factors need to keep pace. Without uncovering and acting upon the opportunities huge information presents, many companies are leaving countless bucks of earnings on the table. The trick to increasing earnings margins is to utilize large information to discover the best cost at the product– not group– level, rather than drown in the numbers flood.

Too Big to Succeed
For each product, business must be able to find the superior cost that a consumer is willing to pay. Essentially, they ‘d consider extremely certain insights that would influence the rate– the cost of the next-best affordable product against the worth of the product to the customer, as an example– and then come to the best cost. Definitely, for a company with a handful of items, this type of prices strategy is simple.

pricing strategiesIt’s additional troublesome when item numbers balloon. About 75 percent of a normal business’s earnings originates from its common products, which commonly number in the many thousands. Taxing, hand-operated techniques for establishing rates make it basically difficult to view the pricing designs that can unlock value. It’s simply as well frustrating for large companies to obtain granular and take care of the intricacy of these prices variables, which change continuously, for hundreds of items. At its core, this is a large information issue.

Lots of online marketers wind up just burying their heads in the sand. They develop prices based on simple aspects such as the cost to produce the item, conventional margins, prices for comparable items, quantity discounts and more. They draw on aged methods to handle the products as they consistently have or point out “market prices” as a reason for not assaulting the problems. Maybe worst of all, they rely on “attempted and checked” historic methods, such as a global 10 percent cost trek on every little thing.

“Just what took place in practice then was that every year we had rate rises based upon scale and volume, however not based on science,” claims Roger Britschgi, head of sales procedures at Linde Gases. “Our folks merely really did not assume it was possible to do it any other way. And, rather frankly, our individuals were not well prepared to persuade our customers of the have to boost rates.”.

Four Steps to Turn Data into Profits.
The secret to much better pricing is comprehending fully the information now at a company’s disposal. It needs not zooming out however zooming in. As Tom O’Brien, team vice president and basic manager for advertising and marketing and offers at Sasol, mentioned of this approach, “The [sales] groups understood their rates, they might have understood their volumes, yet this was something more: very granular data, actually from each and every statement, by product, by customer, by product packaging.”.

Actually, some of the most stimulating examples of making use of big data in a B2B context really transcend prices and touch on various other elements of a firm’s industrial engine. For instance, “vibrant discount rating” provides price support at the level of specific offers, decision-escalation factors, motivations, efficiency scoring, and much more, based on a set of similar win/loss deals. Utilizing smaller, pertinent discount samples is vital, as the factors tied to any one discount will differ, leaving an overarching collection of offers pointless as a standard. We’ve seen this applied in the innovation industry with excellent success– yielding boosts of four to 8 portion factors in return on offers (versus same-company control teams).

To get completely granular, firms should do 4 things.

Hear the data. Setting the very best prices is not a data difficulty (firms normally already rest on a treasure trove of data); it’s an evaluation difficulty. The best B2C companies recognize the best ways to analyze and act on the wealth of data they have, but B2B companies have the tendency to take care of information rather than utilize it to drive decisions. Good analytics could assist business identify just how factors that are usually ignored– such as the more comprehensive economic scenario, item inclinations and sales-representative settlements– disclose what drives prices for every consumer section and item.

Automate. It’s too costly and time-consuming to examine countless products by hand. Automated systems can recognize slim sectors, determine just what drives worth for each one and match that with historic transactional data. This enables companies to establish costs for collections of products and sections based on data. Automation additionally makes it a lot easier to reproduce and fine-tune evaluations so it’s not needed to start from scratch each time.

Construct skills and confidence. Implementing new rates is as considerably an interactions challenge as a functional one. Successful companies overinvest in thoughtful modification programs to assist their sales pressures comprehend and embrace brand-new rates methods. Companies should work closely with offers representatives to clarify the factors for the cost suggestions and just how the system functions to make sure that they trust the costs good enough to sell them to their customers. Equally essential is establishing a clear collection of communications to provide a reasoning for the rates in order to highlight value, and then customizing those disagreements to the client.

Intensive arrangement training is likewise essential for providing sales representatives the self-reliance and devices to make persuading disagreements when talking with customers. The very best leaders come with sales representatives to the most difficult customers and focus on obtaining quick success to ensure that offers reps create the confidence to take on the brand-new prices method. “It was crucial to reveal that leadership lagged this new strategy,” claims Robert Krieger, taking care of director of PanGas AG. “And we did this by joining visits to hard clients. We managed to not only assist our offers representatives however likewise show how the argumentation worked.”.

Actively manage efficiency. To improve performance administration, business should assist the offers pressure with useful targets. The best influence comes from guaranteeing that the cutting edge has a clear look at of earnings by client and that the offers and advertising organization has the best analytical skills to identify and capitalize on the chance. The offers pressure also should be empowered to readjust costs itself rather than relying upon a centralized group. This requires a degree of ingenuity in devising a customer-specific cost method, along with a business mind-set. Incentives could additionally should be changed alongside pricing policies and performance dimensions.

We have actually viewed business in sectors as unique as software program, chemicals, building products and telecoms accomplish remarkable outcomes by utilizing big information to notify much better pricing decisions. All had huge numbers of SKUs and deals, as well as a fragmented portfolio of customers; all viewed a profit-margin lift of between 3 and 8 percent from setting rates at a lot more granular item degrees. In one situation, a European building-materials business established costs that increased margins by up to 20 percent for picked items. To obtain the rate right, business should make use of large information and invest enough resources in assisting their sales representatives– or they could locate themselves paying the higher cost of lost earnings.

Creating the Digital Brain

 

Creating the Digital Brain

 

• FEATURES • By Kaushik Das

 

featured-building-digital-brain

 

Oil spills from mining accidents can cost tens of billions per incident. The famed BP Oil spill in the Gulf cost $40 billion alone for the company, never mind the uncalculated cost of the region impacted.

How could this type of economic and environmental disaster be avoided? Our answer is smart systems. And they are not just a pipe dream, the Pivotal Data Science team has been working hard over the past few years to provide real, practical solutions to answer this type of issue for the oil and gas industry, as well as others.

The idea is to instrument the drilling rig to be a smart system. Drawing on concepts of the Internet of Things (IoT), where any machine from personal wearables, like smart phones and Fitbits, to industrial equipment like jet engines, power turbines and drilling rigs can be constructed as a system of sensors and actuators, essentially creating the the sense organs and limbs of the smart system.  Put these together with the remarkable advancements in big data technologies which enable us to pull petabytes of data into a Data Lake that we can use as a basis to employ complex machine learning models efficiently, and we have the basic two ingredients of a smart system that could monitor and prevent accidents, downtime and even ensure energy efficiency.

Digital Brain = Data Lake + Data Science

How will a smart offshore oil platform work?  Let’s look at the three elements—the sensors, the brain, and the actuators.

The sensors in a drilling rigs measure temperature, pressure, and Monitoring While Drilling (MWD) variables, which can include seismic, gamma ray and high frequency electromagnetic data, as well as hydraulic and mechanical variables.  To create the digital brain, we load all of this data along with measurements made off the drill like those of drilling fluid properties and previous seismic data into a Data Lake.  Here, the all the data is stored together and we can extract patterns in the data.  Since the data for one oilfield involving multiple boreholes can run into hundreds of variables and billions of rows we use a parallel modeling package like MADlib to extract patterns from the data in an efficient manner.  This involves clustering the data and then regressing over the rate of penetration of the drill.

Once we have a good model, we can operationalize it by checking the actual rate against the predicted rate.  If the predicted rate is different, we flag it as an anomaly.  We also create a library of anomalies and label them.  Armed with that dataset, we are in a position to monitor the drilling and take appropriate action if we detect an anomaly.  For instance, if the anomaly is associated with a blowout, we can set the brain to stop drilling by activating the actuators (the control system) and send a red alert to the control room to initiate a response team to investigate.  They may find that this anomaly is just be an indication that the drill bit is wearing out earlier than anticipated and needs to be changed.  Or, importantly, they may discover a serious threat and be able to stop a catastrophe like the BP oil spill.

In the case of the former, this has an added bonus of helping us to do predictive maintenance, and improve the productivity of our operations.  It is an example of the application of Data Science methodology on the appropriate technology.

The Technology Behind the Science

Here at Pivotal we have been making great strides in building the platform that houses the Data Lake.  This includes a parallel storage system based on HDFS with parallel database (namely, HAWQ andGreenplum) and in-memory (Gemfire) modules with a variety of other components that make it easy to ingest and store data, compute on it, and take action.  The whole platform is based on open standards, which makes it highly compatible with a lot of third-party software and effectively future-proofs it.

Centralized_Management

Other Applications for the Digital Brain

Another example of making a system smart would be putting a digital brain into a smart grid.  Right now we have smart meters collecting an enormous amount of data regarding power usage from every business and household.  This maps the entire range of activity in any city!  But how do we get value from that?

The answer is once again to load this data into a Data Lake and look at the frequency content of the time series signals we get from every smart meter.  This enables us to cluster every meter and find out outliers or anomalies.  Then again, as the system tracks the changing of the behavior of a cluster or even individual smart meters, we can identify anomalies as they happen. Over time, we can train our model and label these anomalies as meter malfunctions, meter tampering or vegetation management (a tree or a branch falling on a power line).  Now we have created a Smart Grid than can be our eyes and ears everywhere across the power grid, and can take the appropriate action to prevent downtime and at the same time achieve optimal performance.

Download the Pivotal Data Science Lab datasheet.

The possibilities of the digital brain to transform industry are manifold. We are working steadily to apply this methodology widely, including another industry we are talking about this week at Strata—smart cities and the connected car .

The true potential of the IoT will be realized when we are able to create digital brains and transform the IOT from just things to a self-aware systems.  This will never eliminate the human element, rather it will make human intervention more effective and reduce delays and scope of error in action.

Jeff Immelt of GE has said that “zero unplanned downtime” is a key goal for GE’s use of the Industrial Internet.  But we can take this even further—what about zero unplanned outages, zero industrial accidents and zero environmental disasters?

The opportunity is right here, let us all make it happen!

 

http://brontobytes.info

Utilizing Big Information to Make A lot better Pricing Decisions

Harnessing the flood of information offered from customer communications enables companies to cost appropriately– and gain the benefits.

It’s hard to overemphasize the importance of obtaining prices right. On average, a 1 percent price increase equates into an 8.7 percent increase in running revenues (thinking no loss of quantity, obviously). Yet we estimate that approximately 30 percent of the thousands of prices choices business make every year fail to provide the best cost. That’s a bunch of shed earnings. And it’s especially troubling taking into consideration that the flood of information now available offers business with a chance to make considerably much better pricing choices. For those able to bring order to huge data’s complexity, the worth is significant.

We’re not proposing it’s easy: the variety of consumer touchpoints keeps exploding as digitization gases growing multichannel complexity. Yet cost factors should keep pace. Without discovering and acting upon the opportunities big data presents, numerous firms are leaving countless bucks of profit on the table. The key to boosting revenue margins is to utilize large information to find the best rate at the product– not category– level, as opposed to drown in the numbers flood.

Too Big to Be successful
For every single item, companies should be able to find the ideal cost that a customer wants to pay. Ideally, they would certainly consider extremely specific ideas that would affect the cost– the price of the next-best affordable item vs. the value of the product to the consumer, for example– and then arrive at the very best rate. Indeed, for a business with a handful of products, this kind of prices approach is simple.

pricing strategiesIt’s more problematic when product numbers balloon. Regarding 75 percent of a regular firm’s earnings originates from its typical items, which typically number in the many thousands. Lengthy, manual practices for establishing costs make it virtually impossible to view the prices designs that can unlock worth. It’s just as well frustrating for big companies to obtain granular and handle the complexity of these pricing variables, which change constantly, for hundreds of products. At its core, this is a large information concern.

Numerous online marketers end up merely burying their heads in the sand. They create prices based on simplistic elements such as the price to create the product, standard margins, rates for similar items, volume promos and so forth. They draw on old techniques to take care of the products as they always have or cite “market prices” as a reason for not attacking the issues. Perhaps worst of all, they count on “attempted and checked” historical approaches, such as a global 10 percent price trek on everything.

“Just what happened in practice then was that every year we had price rises based on scale and quantity, but not based on science,” says Roger Britschgi, head of offers procedures at Linde Gases. “Our individuals just didn’t assume it was feasible to do it any other way. And, quite truthfully, our folks were not well prepared to persuade our customers of the should increase prices.”.

4 Steps to Turn Data into Earnings.
The secret to better rates is recognizing fully the data now at a company’s disposal. It requires not zooming out but zooming in. As Tom O’Brien, group vice president and general manager for marketing and sales at Sasol, mentioned of this technique, “The [sales] groups understood their pricing, they may have understood their quantities, however this was something a lot more: very granular information, essentially from each and every invoice, by item, by customer, by product packaging.”.

As a matter of fact, some of the most stimulating instances of utilizing big data in a B2B context really transcend pricing and touch on various other facets of a business’s business engine. For example, “vibrant discount rating” gives rate advice at the degree of individual discounts, decision-escalation points, motivations, efficiency scoring, and a lot more, based upon a set of similar win/loss bargains. Using smaller, relevant offer samples is necessary, as the elements connected to any type of one deal will vary, making an overarching collection of bargains pointless as a standard. We have actually viewed this applied in the modern technology industry with terrific success– producing increases of four to 8 percent points in return on offers (versus same-company control teams).

To obtain completely granular, companies need to do four factors.

Hear the data. Setting the most effective costs is not a data challenge (companies typically already rest on a bonanza of information); it’s an evaluation obstacle. The very best B2C business understand the best ways to analyze and act on the wealth of information they have, yet B2B companies have the tendency to take care of data instead of use it to drive decisions. Good analytics could assist firms recognize just how factors that are often overlooked– such as the broader financial situation, product choices and sales-representative agreements– disclose just what drives costs for each customer section and item.

Automate. It’s too costly and taxing to evaluate countless products by hand. Automated devices can recognize slim sections, establish exactly what drives worth apiece and match that with historical transactional information. This allows companies to establish prices for clusters of items and sectors based on data. Automation also makes it a lot easier to reproduce and fine-tune evaluations so it’s not needed to go back to square one every single time.

Build skills and self-reliance. Applying new costs is as a lot a communications challenge as a functional one. Effective firms overinvest in thoughtful change programs to help their sales forces comprehend and welcome brand-new pricing methods. Companies have to function very closely with sales representatives to describe the reasons for the cost suggestions and exactly how the system works to make sure that they rely on the rates good enough to market them to their consumers. Similarly vital is developing a clear collection of interactions to supply a purpose for the prices in order to highlight worth, then customizing those debates to the client.

Demanding agreement training is likewise crucial for giving offers representatives the self-reliance and tools to make convincing arguments when speaking to clients. The most effective leaders come with offers representatives to the most tough customers and focus on acquiring quick wins to ensure that sales representatives develop the self-reliance to adopt the brand-new pricing strategy. “It was important to reveal that leadership lagged this brand-new strategy,” mentions Robert Krieger, managing director of PanGas AG. “And we did this by signing up with visits to difficult clients. We managed to not only help our offers representatives however also demonstrate how the argumentation functioned.”.

Definitely manage efficiency. To enhance efficiency administration, business need to sustain the sales force with valuable targets. The greatest influence originates from making certain that the front line has a straightforward sight of success by consumer and that the sales and advertising and marketing organization has the appropriate analytical capabilities to recognize and make the most of the possibility. The offers pressure likewise has to be equipped to readjust rates itself instead of counting on a centralized group. This needs a degree of imagination in devising a customer-specific price approach, and also an entrepreneurial mind-set. Rewards may likewise have to be altered together with pricing policies and performance dimensions.

We’ve seen companies in markets as varied as software application, chemicals, construction materials and telecommunications achieve excellent outcomes by utilizing large data to notify better pricing decisions. All had huge numbers of SKUs and purchases, along with a fragmented collection of clients; all saw a profit-margin lift of between 3 and 8 percent from setting costs at far more granular item degrees. In one case, a European building-materials company set costs that boosted margins by approximately 20 percent for selected items. To obtain the rate right, business need to capitalize on big data and spend enough sources in supporting their offers reps– or they could discover themselves paying the higher rate of shed revenues.

Ten Hot Big Data Trends

Ten Hot Big Data Trends

 

01_Hadoop_full

As you enter the world of big data, you’ll need to absorb many new types of database and data-management technologies. Here are the top-ten big data trends:

  • Hadoop is becoming the underpinning for distributed big data management. Hadoop is a distributed file system that can be used in conjunction with MapReduce to process and analyze massive amounts of data, enabling the big data trend. Hadoop will be tightly integrated into data warehousing technologies so that structured and unstructured data can be integrated more effectively.
  • Big data makes it possible to leverage data from sensors to change business outcomes.More and more businesses are using highly sophisticated sensors on the equipment that runs their operations. New innovations in big data technology are making it possible to analyze all this data to get advanced notification of problems that can be fixed to protect the business.
  • Big data can help a business initiative become a real-time action to increase revenue.Companies in markets such as retail are using real-time streaming data analytics to keep track of customer actions and offer incentives to increase revenue per customer.
  • Big data can be integrated with historical data warehouses to transform planning. Big data can provide a company with a better understanding of massive amounts of data about their business. This information about the current state of the business can be combined with historical data to get a full view of the context for business change.
  • Big data can change the way diseases are managed by adding predictive analytics.Increasingly, healthcare practitioners are looking to big data solutions to gain insights into disease by compare symptoms and test results to databases of results from hundreds of thousands of other cases. This allows practitioners to more quickly predict outcomes and save lives.
  • Cloud computing will transform the way that data will be managed in the future. Cloud computing is invaluable as a tool to support the expansion of big data. Increasingly, cloud services that are optimized for data will mean that many more services and delivery models will make big data more practical for companies of all sizes.
  • Security and governance will be the difference between success and failure of businesses leveraging big data. Big data can be a huge benefit, but it isn’t risk-free. Companies will discover that if they are not careful, it is possible to expose private information through big data analysis. Companies need to balance the need to analyze results with best practices for security and governance.
  • Veracity, or truthfulness, of big data will become the most important issue for the coming year. Many companies can get carried away with the ability to analyze massive amounts of data and get back compelling results that predict business outcomes. Therefore, companies will find that the truthfulness of the data must become a top priority or decision making will suffer.
  • As big data moves out of the experimental stage, more packaged offerings will be developed.Most big data projects initiated over the past few years have been experimental. Companies are cautiously working with new tools and technology. Now big data is about to enter the mainstream. Lots of packaged big data offerings will flood the market.
  • Use cases and new innovative ways to apply big data will explode. Early successes with big data in different industries such as manufacturing, retail, and healthcare will lead to many more industries looking at ways to leverage massive amounts of data to transform their industries.

Ten Hot Big Data Trends

Big Data Solutions For 2014

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