Disrupting the Sales Cycle

There is a lot of talk of disruption today, taking old business concepts and shaking up the status quo , by changing the model and re-inventing it. If you are not familiar with the whole disruption movement you check out The Forbes Top 5 technology disruptions from CES.   But there is a school of thought that is showing that disruption is not always the the best way forward, and the current process isn't in need of disruption. Perhaps all we need is just the judicious application of some existing technology and some good old fashioned elbow grease.
Here are some reasons I don't think the Business to Business Sales cycle is in need a of disruption.
The message is simple, B2B sales is, was and should be about bringing value to your client.

1. I don’t believe that most buyers have a linear process. Just like your sales process isn’t linear, and just like you might go over the same ground a few times, your buyer’s process isn’t a straight line from point A to point B, even if we sometimes illustrate it that way to teach some point. If your buyer does have a linear process, it doesn’t always benefit you, and probably doesn’t benefit them as much as they believe it does.
2. There is no way to determine how far a complex organization is into their buying process. I don’t believe suggesting that buyers are 50%, 75%, or 90% into their journey matters very much. Note: We do offer the sales projection and pipeline data that all use these percentages as gospel, but not all business are the same and hence using a percentage may not be a great idea. I was told by a customer the other other , we just put a 1 ,2, 3 in the sales projection because the percentages are really not all that real. The general idea that buyers are more informed is a fact. But every company has a different process, and especially when consensus is needed, it’s messy. The number 50% is no better than the 75% number you use in your CRM/sales force automation software to forecast a deal after you make your presentation (ps we all know you don’t win 75% of those deals)/
3. Except for professional buyers, I don’t believe that most people are spending a lot of time on the Internet researching whatever it is you sell.They’re busy doing their work, and they’re doing so under greater pressure and with fewer resources. If you are professional enough to call and schedule an appointment, it’s likely that they haven’t seen your website.
4. Buyers don’t need to work very hard to find help buying what they need. You are most likely not lucky enough to work in a market where you have few competitors. It’s more likely you work in a crowded market where a lot of good people and good companies sell what you sell. 
5. Most business-to-business sales organizations withhold their insights and share information. Buyers can find a lot of information. But go and look at a large business-to-business sales organization’s website and see how well they fare when it comes to sharing their special insight, the insights and ideas that differentiate them from their competitors. You are far more likely to hear your dream client ask you, “What makes you different?” than “I looked at your website and couldn’t believe how different you are from your competitors.”
6. Most sales organizations that suffer from being understaffed and unable to handle the number of clients beating a path to their door. Almost invariably we see sales organizations that need more opportunities in order to reach their goals. If buyers are doing research, discovering their own needs on their own, developing their own options, and resolving their own concerns, then why aren’t more phones ringing.

If buyers no longer need salespeople, then there is no reason for the popularity of methodologies like the Challenger Sales, insight, business acumen, or situational knowledge. 

Instead, they should be disrupting themselves. Their first step in the buying journey would be recognizing that the status quo isn’t good enough, understanding what new results are already available to them, and searching for potential partners. Perhaps this is sometimes true. But in your experience, how easy is for you to weaken the status quo when you have the knowledge and resources to do so? Do you see the trend shifting are more and more prospects calling on you? 

The Internet is a pipeline and has unlimited potential but it doesn't negate the sales point, by bringing value and becoming the trusted advisor you control and build that sales process. This is not say that data isn’t important or that it isn’t useful.  Rather my point would be using the new tools this technology disruption brings to allow you answer those question , provide those data points to clients and educate them on what others are doing and how the industry is changing. 

As we increasing sell using technology we need to remember that for the most part it's a means to an end and we still need to build on the value that we offer to our prospective clients.

For more information on TSH or MDS call The Systems House, Inc. at 1-800- MDS-5556. Or send a message to sales@tshinc.com

Click here and tell us how we can help you with your business solutions.

Does your company have a data scientist?

Wanted: Data scientists to work on logistics projects

Does your logistics department have a "data scientist" on staff? Probably not.

But if you're planning to conduct a big data analysis to obtain insights into your distribution operations, you'd better be prepared to hire one ... Or make sure you have the right technology partner who can do the job for you. 

 "Data science skills are necessary because the supply chain team is sitting on a lot of unused but valuable data," says Michael Watson, an adjunct professor at Northwestern University and co-author of the book Supply Chain Network Design: Applying Optimization and Analytics to the Global Supply Chain.

A data scientist is someone trained in the methods and techniques for extracting meaning from piles of information. Generally, he or she has a background in mathematics, statistics, and computer science. Although computers and software are powerful tools for facilitating analysis, a human expert is still needed to make decisions about what data to examine and how

"Data science is not a one-size-fits-all approach," says Larry Snyder, an associate professor at Lehigh University and co-author of the book Fundamentals of Supply Chain Theory. "So you can't just throw terabytes of data into an off-the-shelf system and ask it, 'What should I do?' It takes data and decision-making experts to convert raw data into useable information and ultimately, to make decisions."

Companies with analysts who understand your industry and apply real world examples to the data they are examining to draw conclusions. Are the generally the best partners and make a good choice when looking for a data scientist.
Companies like The Systems House, Inc. Target specific industry verticals and have trained data scientists available to assist you in consuming and analyzing the "Big" data that is floating around at your company. 

Because so much raw information abounds in logistics, the discipline is considered to be particularly well suited to big data analysis. Logistics, by its nature, involves numerous data exchanges between multiple partners to make the supply chain flow, and there are piles of raw data sitting in all of those partners' systems. But it's not just traditional data systems that provide fodder for analysis. Big data analysis can encompass information gathered by sensors—say, on trucks or on packages in the warehouse.

The premise behind big data analysis is that if correlations can be made between all that raw data, users can gain a better understanding of why things happen and parlay those insights into process improvements. "Getting to root causes often requires analyzing data to understand correlations—what is related to what," says John Hagerty, a program director for big data at IBM.

Unfortunately, data analysis requires a particular set of skills that most logistics and supply chain managers do not have. "The supply chain team needs to have skills to drill into this data and then the ability to determine what action the company should take based on analysis of that data—the last part is where it is important to have a data scientist on staff," says Watson.

 "The person would be able to sort through the data and help the company determine what actions it should take or how it should build the data into its processes."

Given the boom in corporate interest in big data analysis, data scientists are in high demand right now. In fact, according to the job website Glassdoor.com, the median salary for a data scientist in the United States is currently $115,000.

That's why companies are turning to outside firms to hire data scientists on a project basis.Logistics managers can expect to find themselves in the same situation—that is, in need of outside expertise for their big data projects. That's why the first step for any manager planning such a project may be lining up an outside data scientist for the job.
Companies like The Systems House, Inc. Target specific industry verticals and have trained data scientists available to assist you in consuming and analyzing the "Big" data that is floating around at your company. 

For more information on TSH or MDS call The Systems House, Inc. at 1-800- MDS-5556. Or send a message to sales@tshinc.com

Click here and tell us how we can help you with your business solutions.