Accelerate Sales Improvement By Shrinking Big Data

A colleague once told me that technology without process will just speed up the mess. Forecasts in CRM systems are generated with a few keystrokes but are likely to be as inaccurate as the spreadsheets used years ago when sales managers did “seat of the pants” forecasts, mostly by paring down over-optimistic seller projections.

Selling is the business discipline that has been most resistant to process and technology. Every company implements and enforces stringent procedures for order entry, billing, inventory control, accounts receivable, accounts payable, etc. This shouldn’t be a big surprise because technology works best when there are defined inputs, consistent ways to processes it and measurable outputs.

As relates to top line revenue generation few companies have implemented sales process. As a result sales calls are like snowflakes. No two are the same because of the wide latitude sellers are given in how they sell, how they position offerings, what opportunities they pursue and the progress they choose to report. For many salespeople a high percentage of sales calls are ad-libs. On average sellers achieve quota about 50% of the time. What other area of a business would tolerate half of their staff failing to meet expectations?

CRM software was created to track seller activities and improve pipeline visibility. Without question there is value in centralizing and collecting contact information and sales activities. The problem is that subjective seller opinions about progress on opportunities are the input to CRM systems. The old IT adage of “garbage in-garbage out” applies because inaccurate opinions compromise forecast accuracy. How often do sellers inflate “thin” pipelines? A seller’s primary concern in forecasting is showing adequate activity to keep their managers of their backs, not accurately projecting revenue. 

Years ago I worked with an early CRM provider. Their VP Sales told me by using their software he was +/- 5% in his revenue forecasts, accuracy most companies could only dream of achieving. They had defined eight pipeline milestones. From the first day they joined the company new sellers entered data. Over time each seller’s historical close rates on opportunities were applied to the eight milestones each month to do the forecast.

I asked Phil if his salespeople told prospects their forecasts would be as accurate once the software was implemented. He indicated that they did. We then discussed the fact that his forecasts were based upon heuristic calculations. The software captured how accurate (or inaccurate depending on your point of view) sellers had been in the past and applied their historical close rates to opportunities in each milestone to create the monthly forecast.

New clients would need to gather sufficient data from sellers before forecast accuracy would improve. If sellers left the company their data became irrelevant. When new hires joined, there were lags before their forecasts could be calculated. When new offerings were announced there would be no usable historical data for a period of time.

A colleague once told me that technology without process will just speed up the mess. Forecasts in CRM systems are generated with a few keystrokes but are likely to be as inaccurate as the spreadsheets used years ago when sales managers did “seat of the pants” forecasts, mostly by paring down over-optimistic seller projections.

Attempts to apply artificial intelligence (AI) and analytics to sales have begun. As mentioned before, the wide array of selling approaches, techniques and skills will make interpreting the outcomes of buyer interactions a nearly impossible task. Uncovering best selling practices under these circumstances will be analogous to finding needles in haystacks.

Metaphorically “metal detectors” could dramatically shorten the time needed to evolve best practices if selling could be more structured. This requires a framework of components that are pre-requisites for having a sales process:

  1. Sets of defined milestones for the various types of sales that sellers must execute.
  2. Sales ready messaging® to more consistently position offerings to specific titles.
  3. A common skill set so sellers have the ability to execute messaging and achieve milestones.
  4. Auditability to allow sales managers to grade opportunities based upon buyer actions rather than seller opinions.

As Rita McGrath pointed out in her book The End Of Competitive Advantage, in many market segments product development cycles have shortened to the point where long-term competitive product advantages are becoming a rarity. In many cases it has become an unsustainable strategy.

Analytics and AI are finally making some headway into identifying best practices in selling. Organizations that can accelerate identifying, sharing and evolving best practices can make the way they sell a competitive advantage. Easier said than done, but there are significant rewards for companies that can lead the way in implementing sales process and fine tuning it using analytics and AI.

When organizations know what you’re looking for they’ll find it sooner.

About John Holland

John Holland is Chief Content Officer and Co-founder/Co-author of CustomerCentric Selling®. His primary responsibility with CustomerCentric Selling® (CCS®) is ensuring the core Intellectual Property remains in alignment with buying habits and behaviors. In coauthoring and helping launch CustomerCentric Selling® in 2002, Holland leveraged over 20 years’ experience in sales, sales management and consulting. As a sales consultant, he helped many diverse organizations design and implement sales process. He has worked with technology, overnight delivery, language localization, leasing, temporary housing, corporate relocation and financial services companies in tailoring CustomerCentric Selling® to address their requirements.

John Holland can be reached on LinkedIn and Twitter. Visit Customercentric.com for more information.

 

 


Subscribe to our newsletter

, ,