Preparing Data Before Sales Analytics
by Ian Zhao and Manish Jindal
In Napoleon Hill’s story “Three Feet from Gold”, a gold prospector stumbles upon a shiny ore, but as he digs deeper, the vein of gold mysteriously disappears. The man drills on desperately, but eventually gives up. Later, a mining engineer re-examines the site and finds that since the poor man hadn’t grasped the concept of fault lines, he had stopped just three feet from striking it rich!
Managing an effective sales force is a lot like gold mining in this respect. Persistence is key, but understanding your environment well enough to know exactly where your reps stand in relation to “gold,” or sales deals, is a game-changer. That takes experience and insights from data.
Mining existing sales information can yield great insights. Even for small sales forces, the amount of data accumulated over a year can help answer:
1. Which products sell better than others
2. Who the most effective sellers are, and what they have in common
3. What type of customers are interested in which products
Unfortunately, many companies have not even attempted the basics – not because they don’t have the will or skills, but because analysis is constantly hindered by the ubiquity of “dirty data,” just like fault lines making the vein of gold ore disappear.
Sales data are often gathered without proper quality assurance, resulting in duplicate customer records (e.g., “Cisco Systems” vs. “Cisco”), incorrect units (e.g., $15 instead of $15,000), simple misspellings, and incomplete information... AGI estimates that 15% of CRM entries contain errors. No wonder sales executives often (and understandably) lack confidence in their data, much less the insights garnered from it.
To address data issues, we have many options. Master Data Management is a newly-popular enterprise approach. When time is pressing and a systematic data audit is infeasible, a more practical strategy involves a right amount of duplicate check, missing data imputation (see below), and outlier removal procedures.
Using a recent project for a software company as an example, AGI ran into data issues when modeling customer spending potentials and share-of-wallet. The client data was incomplete and did not map out parent-child relationship among accounts consistently. So we rebuilt the entire account hierarchy by leveraging an external database. But still there was missing data for 20% of customers. That’s when we used the technique of “missing data imputation” to carefully fill gaps in the data with respective industry averages. In the end, we validated our assumptions by comparing the model’s output to actual total market size. The work we did in this project helped our client formulate the right coverage strategy for the right accounts, with a revenue upside exceeding $190M annually!
It also demonstrated that, with the right mix of data preparation and validation techniques, imperfect sales data can still yield impeccable insights to drive sales results.
About the Authors
Ian Zhao is the manager for AGI’s Sales Benchmarking Practice. Manish Jindal is a consultant at AGI’s San Francisco Office.
Companies expect high growth in 2012
The results are in for the Alexander Group's 2012 Sales Pulse Survey. We asked over 100 sales leaders across a number of industries about their outlook for the coming year.
High growth companies are investing more in sales and focusing on customer relationships as a key driver of growth in 2012. Neil Isford, VP Business Analytics & Optimization at IBM, joined me on Monday for a discussion of the New Rules governing sales for 2012. You can listen to our discussion here.
Big Data in B2B Sales: It’s Arrived!
Big Data has become a hot tech trend in late 2011. The term “Big Data” refers to those datasets which are too big to fit into a traditional relational database, and therefore require special tools for data storage and processing. Ten years ago, the only businesses that had Big Data were a handful of financial service, consumer retail, and giant Internet firms, like CapitalOne, Google, Amazon, etc. Those companies relied on massive amounts of data for decision-making. They also had the resources to perform Big Data Analytics properly. With the availability of new IT technologies, especially cloud storage and mobile computing, Big Data is no longer a remote concept for many industries. In fact, it could change the way many businesses are run, comparable to what the PC and Internet have each done in the past.
The Opportunity:
Among all corporate functions, sales may be the one most intertwined with the reality of Big Data. Sales departments generate a lot of data. Let’s use as an example a mid-sized software company’s sales force of 50 reps: one year’s worth of data on things like annual sales contacts, opportunities, and transactions could very easily reach beyond one gigabyte in size. Adding information about products, sales promotions, sales rep compensation and all the various interactions between data points to this mix, it’s feasible to grow that amount of data to a full terabyte. And this is just one year of data! If we retain five years, or ten years of historical records, we are rapidly approaching the limit of some commercial database servers. As you can see, Big Data is closer than one might think. For sales, it may have already arrived without notice. The data is there; the sooner we can dig in to begin exploring its richness, the better we can help answer the types of questions that keep VPs of Sales awake at night, such as:
- Natural market segmentation
- Optimal resource deployment
- Precision quota setting
- Accurate sales forecasting
These topics require rigorous data modeling to address. And sales’ Big Data can help!
The Challenge:
Opportunity and optimism notwithstanding, Big Data also brings serious challenges to sales organizations, especially with regard to sales analytics.
1) Big Data will aggravate the chronic analytical capacity issue. The average ratio of sales reps to sales operations staff is around 25:1. Since sales analytics is a sub-function of sales operations as a whole, we would have no more than two FTEs of analytical resources for a sales force of 50, on average. Those analysts typically have responsibilities encompassing quota setting, territory design, sales credit tracking, pricing approval, answering various questions from the field, etc. What’s left for non-routine analytics is at most 5% of their work time: roughly two hours per week. Even in those precious two hours, sales analysts still need to answer ad-hoc questions from VPs of sales and/or fulfill various data requests from management consulting projects. This is a rather passive modus operandi. No wonder sales operations staff often cite bandwidth as their biggest obstacle to productivity. Without additional investments in analytical headcount, it’s unthinkable that sales effectiveness can improve markedly in the New Era of Big Data, as sales analysts are expected to struggle to keep themselves afloat in the rising ocean of sales data, leaving less and less time for strategically important discovery analysis.
2) Big Data also necessitates the call for major upgrades to sales analytical tools. At present, Excel is still the primary, if not the only, analytical software available to sales departments. Marketing teams, on the other hand, have been using statistical packages like SAS and SPSS to process large datasets and perform automated, specialized analytics (e.g., conjoint analysis, etc.) for more than 10 years. Excel does a decent job of summarizing data and illustrating key statistics using charts. It also has serious limits. By and large, it’s a generic analytical tool which requires a great deal of manual interaction. When data models get too complex, or data changes become too frequent, Excel quickly becomes very clumsy. And complex data models and frequent data changes happen to be two prime characteristics of Big Data. In the face of increasing data variety and velocity, it will be more difficult for sales analyst to deliver timely analytical results using the same set of tools.
3) Big Data requires increased Sales leadership trust in analytics. A study by the Corporate Executive Board indicates that 50% of senior managers from all corporate functions either 1) do not question their data, or 2) do not trust their analysts’ results. Sales leaders tend to fall into the latter bucket. Based on our experience, they are far more inclined to make decisions based on intuition, embracing analytical results only when they support their assertion, and quickly dismissing when they don’t, often on the grounds of “insufficient” or “irrelevant” data.
The Bottom Line:
Properly leveraging Big Data with the right tools and processes in place will effectively disable the ‘insufficient-data’ excuse completely. In order to balance intuition with data-driven conclusions in the presence of Big Data, sales leaders must not only have their sales content knowledge down cold, but also know how to perform basic statistical analyses and database-related IT tasks (e.g., SQL queries, etc.) with speed and confidence.
Sales, statistics and IT are the three essential realms of knowledge for today’s sales leaders, because Big Data has changed the game. Sales may be a people business, but is also a numbers’ game; and just like professional baseball, it needs to be managed by the numbers.
5 Strategies to Manage Seller Bandwidth
14 Executives participated in our 2011 Chief Sales Executive Summit. A big issue on the table - how to manage seller bandwidth in the age of information overload and increasing complexity.
See what they had to say...
Interview with Kevin Warren, President of US Customer Operations, Xerox
In this video from Alexander Group's 2011 Chief Sales Executive Forum, Kevin Warren, President of US Customer Operations for Xerox, shares insight on how Xerox uses a mix of customer feedback, cutting edge sales tools and a multi-channel sales model to help their sales team keep an edge on the competition.
5 Strategies for Profitable Growth in 2012
We're starting the new year off right with some recommendations for readying your sales organization for 2012. Big bets leading companies are considering? Upgrading sales talent, Investing in Front Line Sales Managers, and Re-Evaluating the mix of Generalists and Specialists.
Interested in a briefing to hear more about what leading companies are doing for 2012? Sign up here!
Medical Device Vendors Need New Mix of Field Resources: Part 2
Last week, we discussed the changing role of doctors in the medical device buying process (Read Part 1 here). Let’s turn to another important trend – the consolidation of hospitals and the increasing influence of administrators and procurement personnel in purchasing decisions.
Hospital consolidation and the new buyer. As hospital revenue sources decline (driven by lower utilization, lower reimbursement, and other factors), hospital administrators have gotten serious about improving productivity. Part of the efficiency equation is consolidation through M&A. In 2010, 77 hospital M&A deals worth over $12B were announced, a 33% increase over 2009[1]. Another part of the hospital productivity equation is network expansion. In 2009, 58% of community hospitals were associated with a health system, up from 53% in 2001[2]. For device sales leaders, this continued consolidation means fewer accounts with more buying power.
Coverage Model Impact: To combat the attempts by hospital networks to pass on cost pressure, vendors must deploy a new type of account manager for their most important hospital network accounts. These account managers are problem solvers who contribute across multiple aspects of the hospital network. They are clinically competent, but not necessarily at the same clinical level as today’s field reps. This account manager is expert at selling to the multitude of non-clinical buyers, delivering an economic message, understanding the account’s reimbursement strategy, and providing that baseline level of clinical credibility. This account manager also knows exactly when and how to engage more competent clinical or technical colleagues. This account manager has more in common with successful business-to-business sellers than with traditional medical device KAMs.
To grow in the new environment, device companies must take decisive action to deploy a new mix of sales resources. These resources must help their hospital customers manage through their own upheavals. A tighter focus on expensive field sales deployment is part of the answer. A new breed of account management is another. Together these moves could bring vendors back to double-digit growth.
[1]“Hospital M&A activity jumped 33 percent in 2010” Healthcare Finance News, 2/7/11
[2] American Hospital Association Annual Survey, 2001-2009.
Invest in Sales – It’s Cheaper than Developing a New Product!
Highlights from the 2011 Chief Sales Executive Forum – Part 3 (Read Part 2 of this series)
The sales organization can be considered a “short / long-term” investment. There is the up-front cost of bringing on new reps who may take anywhere from 3 to 18 months to fully produce. But compared to the R&D costs associated with bringing a new product to market, this investment can be relatively minor. The trick is to make sure the positive ROI is in the timeline that you set with your executive leadership team.
Here are some tips from sales leaders at our recent Chief Sales Executive Forum for making and delivering on the case for sales investment.
- Align with Marketing. If you’re planning a new campaign where the ramp time for the sales organization is long, consider a “carpet-bombing” approach with your Marketing counterpart to keep the pipeline filled with new leads.
- Maintain Patience. And Discipline. If your expected ROI is on a 3-year time horizon, keep your executive leadership team focused on the milestones achieved in the business plan, not the short-term dollars coming in. As one sales leader put it, “We include: AND WE MUST HAVE PATIENCE at the end of every presentation as a reminder to the leadership team.”
- Measure More than Revenue. Have a clearly defined scorecard for your initiative with key metrics aligned to your business plan. Hiring a lot of new reps? Include on-boarding, time to productivity, training goals, and other non-revenue metrics to emphasize the process, as well as the results.
What other tips do you have for winning the case for sales investment?
It’s All About the Customer Relationship
Highlights from the 2011 Chief Sales Executive Forum – Part 2 (Read Part 3 of this series)
Salespeople are on the front lines talk to customers every day, but when it comes to “owning” the relationship with customers, they dance a careful tango with Marketing, Product Development, and Customer Service. Leaders from top sales organizations shared their views on the increasing role sales has in building strong relationships with customers across internal departments.
- Mandate Executive Sponsorship. Want healthy customer relationships? Give them someone high up in your organization they can call. One company shared that for their most important accounts, Executives from non-sales departments (think R&D, HR, Operations) own C-level relationships. This helped nervous customers feel that they had a seat at the table as they navigated several big changes in executive management.
- Hire Business-Savvy Client Managers. Customers are no longer willing to have lengthy conversations about their needs. They expect the sales person to understand their needs and offer them a solution with a business case, ROI, and examples of how it’s worked at other companies. Sales leaders need to invest in strategic thinkers who can lead the customer to the solution and provide input into company strategy based on their experience in the field.
- Make a Big Difference through Small Interactions. One company uses real-time communication to send an email to customers post-implementation – click on the smiley face if you’re happy, do nothing if there are no problems, and click on another button to report an issue. The result? Improved customer satisfaction and a better ability to anticipate their customers problems and needs.
- Involve Product Development. One way to improve communication between product and sales teams is to move product development into the commercial organization. One company found this created a much better feedback loop between customers, sales, and the development team, although they still haven’t fully “cracked the code” on minimizing one-off requests for additional features.
What is your sales organization doing to listen to your customers? Do you agree that Sales has a bigger stake in “owning” the customer relationship? (Read Part 3 of this series)