Inspiring the right sales behaviors with incentives that matter


“The sales performance management market grew 14%, to $1.099 billion, in 2019.”

                                                 Gartner Magic Quadrant for Sales Performance Management, 2020

There was a time when prospects were completely dependent on their sales representative’s advice and expertise to take the final purchase decision. For the sales team, incentive structures were simple and directly proportional to the number of units sold. With the dawn of the internet/information era, the role of sales reps changed drastically, with a lot of new variables like  external market, competition, internal influences, and trade policies coming into play. The elite and educated consumers present a higher resistance to traditional selling efforts. And, in the last year, with little or no face to face client discussions and longer than average buying cycles, the sales reps’ job became tougher than ever before. In a similar vein, designing a sales incentive mechanism has become tedious and over complicated, leading to  poor sales motivation and even poorer results.

Designing an optimized sales incentive mechanism

“By 2022, 40% of B2B companies with over 100 payees will deploy SPM solutions to reduce hidden incentive compensation overpayments.”                                                                                                                                     Gartner Magic Quadrant for Sales Performance Management, 2020

Sales leaders are always looking for the optimum combination of individual selling, team collaboration, organizational objectives, and growth to design modern incentive plans. Teaming these with the right sales behaviors that overcome competitive pressures and drive enhanced customer experience is again not very easy with rigid incentive plans. Overcompensation is another big challenge in designing such plans. Here are four key aspects of an effective enterprise incentive management and sales planning tool.

  • Quick incentive calculation

This is a key requirement of the incentive management solution as accurate and timely incentive payouts go a long way in boosting seller motivation. Leading tools have the capability to automatically import HR data, ensuring that employees are compensated on time for their respective roles. They also optimize the speed and accuracy of compensation data by automating complex calculations that ingest multiple input data at an individual, divisional and organizational level.

  • Real-time visibility

The incentive solution should provide real time access to sales performance. This empowers both sales leaders and the frontline team to take quicker action and meet organizational objectives. Access to sales performance data and compensation structures also minimizes internal disputes and facilitates the sales leadership to intervene and take corrective action when needed.

  • Scenario planning

Some of the leading incentive management tools in the market allow the modeling of multiple potential compensation structures and assess their effectiveness before rolling them out to the sales team. This enables the study of potential changes and their impact on the plans. Models with different combinations of territory and quota information allow quick modification of compensation plans to drive business priorities at a particular point of time. 

  • Predictive analytics

Integration of intelligence in the incentive management solution can help forecast compensation earnings and quota attainment trends. These, in turn, help allocate budgets and take preventive/precautionary measures in case of not so positive forecasts. Analytics also help sales leaders determine whether the program is giving the desired results, enabling the sales team to achieve their targets, delivering enough returns, etc. Predictive analytics solutions see much higher trust and accountability with the sales team.

Quicker incentives drive sales culture – A case in point

A top telecommunications company was unable to scale up their sales reporting process which took an average of three weeks. Their outdated, manual systems inhibited the free flow of information, increasing call center interactions from . Adopting a simple and efficient incentive management solution allowed real-time visibility into sales and incentive data, bringing down sales reporting time to one week. The system also reduced error in payment margins from >10% to <1%, and enabled quality incentives based on sales tactics. All these highly improved sales morale and enhanced team performance.

Rewarding deserving sales behaviors

Incentive structures should first achieve what they were primarily designed for, that is motivating sales folks to add to the top line, become the successful interface with the client while furthering the organization’s larger business objectives. An optimized incentive solution will ensure a fair compensation and reward deserving employees. The key would be to identify and retrofit one that matches the unique challenges and requirements of an enterprise.  

Sales Forecasting: The crystal ball for sales leaders. Spearheading sales success – The role of forecasting

“The global potential market for copying machines is 5,000, at most.” IBM to Xerox in 1959.

After launching the first copier in 1959, Xerox garnered revenues of over $500 million in five years’ time. It is hard to overstate the importance of an accurate forecast. IBM’s legendary statement to Xerox in the fifties is a case in point.  Sales teams worldwide have relied on market forecasts for a better understanding of the organization’s go-to-market efforts. Although recent world events make forecasting a herculean task for all involved, accurate forecasts are not only a means of generating higher revenue, but they also lend credibility to the forecasting organization/solution in the market.

Sales forecasting data finds value across the enterprise. While the sales function leverages it for revenue generation from new accounts and to maximize cross-sell and up-sell opportunities from key accounts, other functions also find forecasts effective.  Planning of production cycles, setting financial budgets, material purchases, territory planning, channel partner strategies, and many other key enterprise activities rely on accurate forecasts. Let us look at forecasting from the viewpoint of the sales leadership and how a dynamic forecasting tool can support that agenda.

Chief sales and revenue officers bear the primary responsibility of enhancing enterprise profitability and growth. The organization looks up to them to provide direction on when, how and with what to enter new markets, as they strategize on ways and means to achieve corporate objectives. An accurate sales forecast empowers sales leaders in strategic decision-making as they have precise insight into sales numbers vs. market performance.

Simple, predictive and iterative – Three must haves for forecasting success

With increasing complexities of business and technology ecosystems, simplicity is evolving as a key mantra for enterprise leaders. Sales leaders are more than ever on the lookout for forecasting solutions that can enable them to access market and sales insights intuitively without much technical intervention. Tools that don’t require technology expertise in terms of configuration, deployment or operation are highly favored for their ability to give access to insights and allow easy conversion of customer data, while bypassing tedious data preparation processes. Understanding key data drivers simplifies strategic decision making.

Modern forecasting tools that leverage machine learning capabilities have the ability to Such tools enable sales decision makers to evaluate diverse scenarios, using huge volume of data, and drive future outcomes with high accuracy. The sales teams can be made more accountable for sales closures, and sales leaders can better identify potential risks and over-commits. As the volume of data increases with continuous usage, the accuracy of future forecasts improves over time.

Many organizations also look at developing a forecasting model that can be customized to their unique requirement. In such a scenario, an iterative, detailed and expertise-driven approach can be taken with the right tool. Running automatic analysis on huge volumes of data can uncover unseen insights. The sales leadership can then choose the best model for their needs, tie forecasts to territories, quotas or incentives, and analyze trends over time, regions, teams, or products. The iterative nature of the forecast ensures continuous learning as the forecast capability evolves over time to deliver further enhanced insights.

A success story

A top global software and cloud computing company was facing several sales constraints – unoptimized territory planning, high cost of sales operations and random budgets that were not aligned to revenue targets. Implementing a dynamic sales forecasting solution, the software giant was able to bring down sales coverage across 1,000 territories by 40 days, with granular insights into sales regions and sub-regions. Dynamic scenario planning enabled faster closures on sales quotas.

Future forecast

Sales forecasting enables the creation of a realistic picture of what to expect in the immediate future, not having an optimum model for the same can prove to be costly for businesses. However, with the surplus of tools available in the market it is not easy to select the one most relevant for the business and its unique requirements. Data driven sales forecasting tools can deliver better outcomes, empowering the sales team to provide accurate deal commits and closures.

The insights approach to sales planning success

“The power of selling is moving away from the individual and toward the machine – machines that can now prospect, follow up, present, and propose without human intervention.”

Victor Antonio, bestselling author, sales trainer and motivational trainer

AI powered sales planning

As artificial intelligence (AI) infiltrates into every aspect of modern life, leading organizations are quick to adopt this disruptive technology to influence key elements of their sales planning and strategy. An enterprise sales function typically pursues three key avenues for achieving set revenue targets:

  1. Acquiring new logos that translate to selling more products or driving higher margins in new accounts
  2. Expanding to new markets with the launch of a new product, or launching an existing product in a geographically different market
  3. Retaining key accounts and minimizing customer churn through active renewals, cross-sell and up-sell efforts

AI intervention can impact each of these three key areas transforming not only how customers buy products and services, but also how organizations can better control the sales outcome. Predictive sales planning tools blend the known attributes of the account or customer such as company, industry, purchase history, spend, usage, adoption, and so on, with unknown factors of growth, partnerships, hiring trends, tech stacks, install base, solution intent, etc., to provide deeper insights. Let us look at some of the key traits of such a solution:

Account segmentation and lead scoring

Sales teams often make the mistake of scoring leads based on inadequately interpreted buyer signals and gut impulse, which totally defeats the purpose of lead scoring and account segmentation. AI empowers businesses to enhance their segmentation and scoring activities by simply augmenting internal data with predictive attributes on profile fit and buyer intent. Thus, businesses are in a position to accurately determine the outcome of sales opportunities, and focus their time on the more lucrative leads and accounts.

Sales territory planning

Sales territories have a big impact on the performance of the sales organization. A good understanding of the sales potential of different regions is vital for sales success. Equally important is ensuring a fair distribution of territory among the organization’s sales representatives. This provides every rep an impartial opportunity to achieve their quota. Predictive insights in territory planning can help alleviate these challenges and improve morale and performance of the sales team. Leveraging AI, territories can be carved across the multiple dimensions of geography, industry, product, key account, etc. This ensures a balanced approach to territory planning based on historical data and total market size.

Balanced quota planning

Setting sales quota is a tough balancing act for sales leadership, as it is directly tied to the sales professional’s compensation, morale and overall growth. Incorrect quota planning might impact all the three, set the salesperson on a downward spiral and also hit revenue targets. Intelligent quota allocation leverages predictive insights that empower sales leaders to design effective quota planning; setting achievable targets and quotas and in turn motivating sales people to achieve revenue goals.

Sales capacity planning

Sales leaders are always looking for ways and means to maximize revenue. An oft overlooked and underutilized approach is that of capacity planning. Knowing which roles to hire, when to hire and determining the optimum sales capacity to achieve organizational outcomes are critical components of successful planning. An ideal capacity planning model can enable sales leaders with deep insights into strategies for enhanced sales coverage, capacity and gaps across channels and help improve sales productivity.

Kick start sales with the right planning

These are just a few key areas to start with. Adaptive and intelligent sales planning solutions can enable myriad perspectives with sales KPIs and analytics, sales coverage, objectives management, pipeline optimization, and a lot more. Leveraging data as a strategic asset across the organization, such solutions can create better, faster and stronger frontline sales with collaborative planning, accurate forecasting and enhanced sales potential.

Resilient and responsive S&OP- The force behind successful Supply Chains


The new normal is testing supply chain resiliency and organizations are forced to revisit their demand and supply operations and drive new revenue streams. Sales and Operations planning (S&OP) typically face time, people and monetary constraints. As the new unexpected global crisis tossed aside months of careful planning, business executives were forced to go back to the drawing board, re-planning using traditional tools and solutions. This highlights the glaring gap in S&OP planning as organizations increasingly look at making strategic and data backed decisions now and in the near future.

The need for speed in S&OP decision making

Sales success invariably depends on integrating the right sales behaviors with real-time planning and analytics to maximize returns. S&OP is the backbone for the entire organization, more so in times of crisis, and hence the process needs to build in inherent resiliency and be ready to respond in any situation. Here we look at a few simple tactics to create S&OP processes that stands the test of time.

  1. Integrated S&OP platforms

To empower S&OP teams to make sophisticated planning decisions, and meet continuously changing business realities, the first step is to do away with the decision latency associated with multiple, disconnected supply chain planning systems. Incomplete S&OP processes are more often than not a result of disconnected sales/marketing, finance and other internal systems. A unified platform goes a long way in enhancing collaboration and aligning decisions across departments. An easy-to-use collaborative platform can not only improve service levels and plan accuracy through better customer and supplier collaboration, but also helps maximize market opportunity, profitability and customer satisfaction while reducing supply chain risks.

  1. ML based forecasting that takes accuracy from good to excellent

“The traditional monthly S&OP cycle will no longer cut it. Rapid re-planning and in-cycle adjustments will become the norm.”  Mark Hermans, Managing Director at PwC, Aug 2020

The COVID-19 crisis has well exposed the vulnerabilities of traditional statistical models that cannot portray previously unknown demand patterns. To increase planning efficiency, it is a must to create capabilities that can take into account an entire ecosystem on-demand. There are tools in the market that has the ability to ingest up to multiple data inputs and greatly enhance the quality of the forecast. Inbuilt ML capabilities train forecast models to deliver more tailored outputs. This enables S&OP decision makers to acquire a better understanding of future drivers, predictions, and the impact of different “what-if” scenarios.

  1. Robust, accessible and simple

Many a time the inherent complexity of an S&OP platform dissuades users from leveraging the same to create meaningful reports. Thus, they are left hanging in the face of supply chain disruptions with no ability to anticipate the sudden demand changes. This highlights the need to adopt tools that simplifies the process, allows flexible modeling, and provides a better user interface. Such a tool doesn’t require any intervention from data scientists or ML experts for configuration, deployment or operation, empowering users to go the full length and unlock intelligent insights. Sales teams can also leverage the platform to easily convert customer data into a format that is forecast friendly thus avoiding tedious manual data preparation

S&OP transformation: Infusing resilience and agility

Supply chain resilience is an outcome of an organization’s S&OP resilience.  Transforming the S&OP process not only acts as an insurance against future disruptions but also enhances the daily planning activities. Infusing agility into S&OP improves collaboration among sales, product, innovation, finance, operations, and marketing units, increases productivity with improved processes, facilitates better understanding of the underlying risks and opportunities, and help teams make more informed predictions while expending fewer resources. With detailed P&L interactions, intuitive scenario planning, and near real-time supply-demand balancing at their disposal, such teams are a step forward when it comes to quickly and nimbly responding to supply chain emergencies.

Thanks to COVID to make us realize the reality of Supply Chain Disruptions and how we can work towards mitigating the Supply Chain Risk

Holiday demand planning: Three key attributes for speed & accuracy

Season’s Greetings! Brought to you by Solvanni

It is that time of the year again; and the retail, consumer goods, F&B, and logistics industries are eagerly waiting for consumers to splurge, despite the recent dip in global economies. It is also the most dreaded time for supply chain leaders across the globe, all except Santa. He’s probably the only supply chain leader who not only knows when you’ve been good or bad, but his demand forecasting system works so well that everyone receives their presents on Christmas day, every time! But for lesser mortals, this isn’t the time be bogged down by glitches, human or technical. Most CXOs would remember candy giant Hershey’s horrific Halloween of ’99 when they could not deliver $100 million worth of Kisses and Jolly Ranchers. No one would want to get caught in a spot like that. *


A recent survey by Deloitte indicated that 65% respondents preferred online shopping to avoid crowds. While this doesn’t come as a surprise in the current times, this holiday season will be a witness to new challenges and roadblocks as organizations bravely prepare to meet the demand surge. Especially when most global sourcing, manufacturing, transportation, and last mile delivery organizations are not out of the rut yet. In light of the new supply chain challenges, on-time delivery will see a new low. Salesforce predicts that 700 million gifts will not arrive in time for the holidays.

The dynamics of Demand Planning

Demand planning has never been an easy job. Planners have to factor in a lot of variables, coordinate across business key business functions of Sales, Marketing, HR, and Finance, understand demand patterns and market conditions that impact those patterns. Successful demand planning demands being proactive and prepared for dynamic markets shifts, such as the impending holiday season. All of these are possible only when there is a free flow of information across the organization. There are several tools in the market that leverage historical data to generate market forecasts. However, the biggest challenge with most is their inability to deliver accurate forecasts in case of unforeseen market/economic conditions such as the current situation.  Let us look at three key attributes of a demand planning tool that are critical in the current times.

  • Address multiple types of datasets

Many commonly available forecasting tools generally use a single type of data, which is in most cases enough to deliver a forecast. Some new tools can compute with multiple types of data, delivering a more accurate prediction. Additional data sets can help create more customized forecasts, applicable to specific scenarios, with continuously improving accuracy of the forecasts, much needed to manage demand efficiently during the holiday season.

  • Run ad hoc analysis

Almost all forecasting systems available today provide an accurate picture of the future. But there are only a handful of tools that can delve into the drivers that result in a particular prediction. The ability to run such ad-hoc to perform analysis on your data is a powerful mechanism to analyze the forecast from multiple angles and thoroughly study the drivers that have the most impact on the forecast outcome.

  • Democratize forecasting

Analytics and Machine Learning (ML) have traditionally been viewed as the stronghold of data scientists and experts with special degrees. An innovative forecasting model should be able to drive AI & ML capabilities across the organization while enhancing the efficiency of the specialists at the same time. Such a tool democratizes ML forecasting, providing quick and easy access to the insights to whoever needs it within the organization, thus empowering more people to drive value and handle seasonal spikes with ease.

Powering order fulfillment beyond 2020

It is not just Santa who needs an effective demand planning mechanism; accurate forecasting is a must for successful supply chain dynamics. We will see more uncertainty in the times to come with strained geopolitical relations and economic instabilities. Resilient supply chains and empowered leaders with strong decision-making capabilities will leverage technology to drive real business outcomes in the future of successful demand planning.