B2B-client-centric-growthIncrease Sales Win Rates, C-sat with Better Targeting & Skills

Background:

A leading group company involved in Engg and Enterprise Solutions for manufacturing sector to group companies & 3rd parties wants to increase sales win rates, C-sat with better targeting and skills and thus improving its client centricity

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Big 4 Actions:
Background:

A leading independent terminalling company wants to achieve seamless delivery during build and operate and thus improving client centricity

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Big 3 Actions:
Background:

An ITES arm of a big software company which works with enterprises across industries wanting to improve its client relationship

Condition:

One of their large account ($1Bn) wanted to terminate their enterprise contract due to issues with ITES services. Hence main focus was to prevent the churn by short term fix and long term actions.

Big 5 Actions:
Background:

A leading business services firm provides B2B telecom Solution and services in India wanting to improve responsiveness in pre-sales

Condition:
Big 5 Actions:
Background

A leading global ship management company with 600 ships under management and 24k seafarers wanting to strengthen is ‘competence’

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Big 5 Actions:
Improving Your Organization's Sales Analytics Capability

Improving Your Organization’s Sales Analytics Capability

With the advent of Big data and Analytics, every single discipline of business entities have seen tremendous benefits derive out of data based insights. While Analytics has penetrated Operations, Supply Chain, Marketing, HR, and IT, one of the biggest beneficiaries that directly contributes to the top line of the organization is Sales Analytics. Marketing Analytics & Marketing Automation has ensured high return on investment for the marketing costs, increasing reach and quality of marketing communication. The demand so generated through effective marketing has to be converted to business volumes. This is where Sales Analytics plays a big role. Sales processes are quite complex, involving various partner organizations, internal functions, several legal and regulatory requirements. Adding to this complexity are factors such as engagement of off-role employees, high staff attrition, competition activity and economic conditions.

Sales Analytics plays a significant role in this pursuit. The dynamics of sales data and the factors mentioned above, demand that Sales Analytics be approached a little differently from other analytics programs such as Supply Chain or Operations Analytics. Traditional focus has been on acquiring an efficient Sales Analytics Solution, Sales Process Automation and Sales Intelligence technology tool. There are a variety of products in the market with incredible capabilities such as SAP Business Objects, Oracle Business Intelligence, Salesforce Wave analytics, Alteryx, Tableau, Qlik Sense Enterprise, Sisense, Microstrategy, etc.,

However, now-a-days, the business benefits from Sales Analytics are not usually constrained by technology capabilities rather by other factors such as:(arranged in no specific order)

Unfortunately, leaders spend too much energy in selecting the right technology tool only to realize their team members aren’t ready for a heavy dose of data driven insights or ecosystem isn’t ready.

Data Quality & Data Governance

It’s no secret that sales data quality is a challenge as it involves partners, customers and external factors. Though hand-held devices, cloud storage and real time analytics tools have made eased things, no one can disagree that getting data that is reliable isn’t easy in sales. Further, many times it is difficult to audit its authenticity. Read More about the Importance of Data Quality & Data Governance for Sales Analytics.

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Conviction of Sales Leadership towards data based selling

Sales is considered an art and building relationships with customers is considered as an enabler. Many Sales leaders don’t believe in looking beyond sales numbers. Metrics and data that provide insights and help us identify drivers aren’t given too much importance. Without this conviction, it is very difficult to see any real ROI for Sales Analytics investments. In fact, this is a show stopper. Read More about the Tips to build Sales leadership buy-in for data based selling through Sales Analytics

Sales Analytics Talent & Capabilities

In order to fully leverage Analytics and Big Data, Sales leaders need to build skills & capabilities among sales teams that include Quantitative Skills, Data or Fact based Decision Making & technical skills, Data based Problem Solving which will help them to decide what data is needed in any given scenario, framing hypotheses and validating the hypothesis through data. Read More about What specific analytical skills are needed for Sales Managers in the era of Analytics?.

Cross-functional Alignment

Prima facie, Sales Analytics seems to be an internal matter of the Sales function.However, true and meaningful Sales Analytics will require strong alignment of various functions such as Marketing, Supply Chain, Manufacturing, Quality, Product Development, Service, Business Planning, HR, etc. Studying the association of cross functional factors on Sales or Business Outcomes such as Market Share, Revenue, Profitability is very important. This means cross functional data sources will need to be analyzed in Sales Analytics. Read More about Non-Sales Data & its value in Sales Analytics.

Thus Building Organization’s Sales Analytics Capability needs a thoughtful & comprehensive approach.

If you are looking for Sales Analytics Training and consulting in Chennai, Bangalore, Mumbai, Delhi and across India, contact us.
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Nilakantasrinivasan J

#nilakantasrinivasan-j #canopus-business-management-group #B2B-client-centric-growth #sales-analytics #salesforce

5 Reasons to Up-skill Sales Teams on Sales Analytics

5 Reasons to Up-skill Sales Teams on Sales Analytics

The last 2 decades experienced a sea-change when it comes to how organizations handle business development. While ERP and CRM put process rigor and discipline to the sales management process, the era of Data Analytics, Big Data and Cloud Computing have empowered sales managers with data that can enable them to make informed decisions. The future looks exciting with 5G mobility, Machine Learning, AI and Quantum Computing bringing in more and more information & insights, instantly for decision making. However, such opportunities come with their own share of risk and threat. Sales Managers who used to bank on their interpersonal skills, negotiation skills, etc., to deliver stellar performance have to accept that without adequate up-skilling on Sales Analytics, their extinction is indispensable.

Here are top 5 reasons to up-skill sales teams on sales analytics:

1. Analyze Data Independently and Save Time

Many sales managers lack sufficient data analytical skills. The skill sets are vastly across organizations. Some can’t make charts in excel while others are more versatile. It is not an aberration to state that most of them cannot independently analyze data to come up with breakthrough insights. They are either dependent on the sales analyst or their managers to provide them an action plan, given a scenario. 

Today, ample data is available in finger tips and business intelligence (BI) tools are also within reach of every employee. Analytics savvy sales managers utilize these resources to independently analyze the data to define problems, identify factors driving the problem, unearth patterns in the data for planning and execution purposes. They not only save time due to reduced dependency on others but are also more confident because it’s backed by data or facts.

2. Ask Right Questions and Take Informed Decisions

Many times sales managers deal with ambiguous situations such as lack of information on competition’s plan, customer’s behaviours, economic drivers, product acceptance in the market, etc. Asking the right questions, at the right time, to the right person gets the right answers. Those who are skilled in Sales Analytics will analyze the data to understand the situation better,  frame questions or problems that are specific and relevant to the circumstances. Without doubt, this will enable them to become better decision makers.

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3. Identify Opportunities/Root Causes Early and Improve Business Performance

Locating an oasis in a desert is much easier with a satellite imagery. It can pinpoint exactly how to get there faster too. Solving problems in sales and unearthing business opportunities are much easier with data analytics. Sales managers with Sales Analytics skills are 3 times more likely to tap on opportunity or solve a problem than those without such skills. 

4. Communicate and Convince Stakeholders

Sales folks are brave hearts who deal with objections and resistance day in, day out. Whether it is a client, business partner, sales director, internal stakeholders such as supply chain, product development, marketing, etc, they are more likely to convince such stakeholders with insights, charts, evidence, etc than otherwise. Storytelling, backed with data and analytics is more likely to get buy-ins, approvals, endorsement and support.

5. Become a Future Fit Business Leader

The business world looks very different from it was 2 decades ago and be assured it would be even more different in the years to come. Digital transformation is being led by data, analytics, cloud computing and fast networks. Sales and business leaders are expected to only be an active user of data and analytics but become a power user to survive in future..

If you are looking for Sales Analytics Training and consulting in Chennai, Bangalore, Mumbai, Delhi and across India, contact us.
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Nilakantasrinivasan J

#nilakantasrinivasan-j #canopus-business-management-group #B2B-client-centric-growth #sales-analytics

Sales Problem Solver's Skills

Sales Problem Solver’s Skills

We all are problem solvers at our own level. Handling challenges, hurdles, persistent issues and alleviating them is what differentiates a great sales manager from the rest.

Tools and techniques for solving problems are well established for a long time now and there are various methods, techniques and tools that can be used. For example, Lean Six Sigma, TQM, Agile, Scrum, Design Thinking, etc are few such frameworks. Various sectors have seen success with these methodologies. However, when it comes to functional success, business development and sales is a unique function in that, it is highly dependent on external factors. Even many internal factors are not within good control of the sales organization. Thus, there are certain unique challenges that sales managers face when they try to apply such proven problem solving methodologies for sales problems.

More than a structured approach or framework for solving sales problems, the first thing Sales Managers should develop is a Sales Problem Solving Mindset. The skills that support this mindset are described below. Each of these skills can separately add value to every sales manager’s performance. When applied in the form of a structured problem solving framework, it becomes very powerful.

Problem Framing Skills

The first step in solving business problems is knowing exactly what is the problem that has to be solved. This might sound like a no-brainer. But don’t underestimate the power of clarity. If the organization wants to improve its market share in a particular segment, the problem may have to be framed keeping in consideration points such as – Is our market share very low compared to peers, how long has it been this way, what have we done and why have they failed, what is the customer’s perception about us?, etc. After sufficient exploration, we may narrow down and define the problem that we wish to solve as “How can our employees engage with our channel partners effectively?” instead of “How to improve our Market Share?”

Sometimes, we can define the problem and then collect data, but on other occasions, we have to do the reverse.  Thus framing a problem for a given scenario is a skill in itself and Sales Managers need to master this.

To register to our online ‘Sales Managers Problem Solving Skills Course’.
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Data Collection Skills

In order to permanently solve any problem, we need to go to the root cause of the problem, and use data or facts to validate really if a particular cause is the reason for the problem. Often, Sales Managers are plagued by reasons that their team members use to justify their poor performance. But these have to be validated with data. Unfortunately, the problem in sales is that required data is not often available. Sales managers should develop necessary skills to understand what data is needed to validate a given problem or cause and how to gather that data. Sometimes surrogate measures will have to be used and sometimes they have to live with surveyed data. Thus the ability to know what data is needed in a given scenario and how to gather that is the second skill needed for Sales Managers wishing to solve business problems.

Quantitative Analytical Skills

Today’s sales enablement systems such as CRM, ERP, etc provide enough data to get started with some basic sales analytics. However sales managers need to upskill themselves in analytics. They need to know how to perform necessary analysis from the data available. While Sales Analysts are well versed in crunching numbers and preparing charts, many Sales Managers are not even comfortable with relevant formulae and charts in Excel. The ability to work with data, using visualization methods to validate association or relationship between various factors, use statistical tools to identify sources of inconsistency in performance & factors driving it, ability to identify known best performers from data, using probability principles to validate demand-supply problems in sales and statistical association/correlation studies to identify causes are all essential analytical skills for sales managers.

Qualitative Discovery Skills

To solve most sales problems, an augmented approach of using both Data and ‘Gemba’ is needed. There are several aspects such as field observation, validation or audit of sales standards across the sales process, partner sales rep skill and will validation, qualitative evaluation of customer objection handling, benchmarking competition best practices, picking up verbal and non-verbal clues, etc., that require strong discovery skills that sales managers need to develop.

Experimentation Validation

The willingness to accept that not everything that we are doing is going click & that too the very first time is the basis for experimentation validation. When solutions are put in place, often sales managers are anxious to see the results right away. In reality, many of our action plans are unique to the circumstances and the mindset to see it as a series of experiments and set logical check points, learn the lessons and move forward to refine the action plan or solution is any skill that sales managers need to acquire too.

If you are looking for Sales Analytics Training and consulting in Chennai, Bangalore, Mumbai, Delhi and across India, contact us.
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Nilakantasrinivasan J

#nilakantasrinivasan-j #canopus-business-management-group #B2B-client-centric-growth #sales-analytics #sales-problem-solving


1. Improve Recruitment Effectiveness

HR analytics lets HR make better decisions on the basis of historical information of employee performance. For example, if data suggests that some of your best talent have certain education background, hobbies or profile, you will be able to screen profiles from the candidates pool and get those who are most likely to be successful. This would mean lower cost of recruitment, reduction attrition in future and better business results.  The availability of online databases, applications, profiles in social media and career directories, documents, etc. today enables how we can improve the effectiveness of recruitment and easily learn more about applicants.

Similarly, we can use online databased and career directories to build profiles and job descriptions based on how other organizations define such roles and the availability of talent pool in the market. This is higher success rate during not only recruitment but also in retention

2. Build Productive Workforce

Using historic data of employee performance and specific conditions that led an employee to performance better, HR managers can using Clustering Models to put together teams of like minded employees where every individual performs it his/her best. Similarly, inconsistent performance, spikes or drops in performance can help HR analysts identify key drivers for such pattern.

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3. Reducing Attrition by Predicting it

This is one of the most widely used application or example for HR Analytics. By using historic data related to employees it is possible to used Machine Learning (ML) classification models is very accurately predict employees who are most likely to leave the organization. This is called as Predictive Model for Employee Attrition. The model provides the propensity or probability that an employee would leave in near future. This data based approach can replace RAG (Red/Amber/Green) colour codes that HRBP’s use to classify employees based on high flight risk.

4. Performance Management

Linking Performance to Pay is a ever green topic in HR. With performance data that goes beyond performance rating, C&B professionals can build statistical models to validate if the increased compensation and benefits to an individual can result in justifiable business performance improvement. Further data analytics can be used to profile employees based on the value they see various benefits provided by the organization and personalize the package.

5. L&D Effectiveness

L&D can play pivotal in enhancing business performance and building a future fit workforce by using the data to identify training needs, establish quantitative effectiveness measures for L&D interventions and statistically prove effectiveness of the program. For example, using wearables, L&D professionals can capture real time data of employees heart rate, to ascertain the effectiveness of the learning module covered in training. Data can be used to design effective intervention. 

And most importantly, L&D can rescue themselves from the perception of being providers of different career development programmes that deplete a large part of the company’s budget.

Nilakantasrinivasan J

#nilakantasrinivasan-j #canopus-business-management-group #B2B-client-centric-growth #HR-analytics

In the recent years, most business functions have undergone a transformation because of the power of Big Data, Cloud Storage and Analytics. The Digitization wave that is sweeping the industry now is nothing but an outcome of the synergy of various technology developments over the past 2 decades. HR is no exception to this. HR Analytics and Big Data have provided the ability to HR leaders to take “intuitions” out of their decisions, that have been the norm before and replace that with informed decisions based on data. The use of HR analytics has made official decisions more promising and accurate.

For this reason, today many companies invest tremendous resources on talent management tools and skilled staff including data scientists, analytics and analysts.

Nevertheless, there’s a lot more to do in this area. According to a Deloitte survey, 3 out of four businesses (75%) believe the data analytics use is “important” but only 8% think that their organisation, is strong in analytics. (The same figure as in 2014).

HR Analytics can touch every division of HR and improve its decision making including Talent Acquisition and Management, Compensation and Benefits, Performance Management, HR Operations, Learning and Development, Leadership Development, etc. .

Most organizations today sit on a pile of data, thanks to HRMS & Cloud storage. However, in the absence of a proper HR analytics tool or necessary capability in HR professionals, these useful data or information we are talking about might be scattered and unused.  Organizations are now getting to accept that Analytics is more about capability and less about acquiring fancy technological tools.

A HR Professional with right Analytics capability can interpret and transform this valuable data in useful statistics using HR and big data analytics to insights. HR will determine what to do on the basis of the results until trends are illustrated. The impact of HR metrics on organisational performance is analysed using analytics and that can enables leaders to take proactive decisions.

HR Analytics can also help in addressing problems that organizations face. For example, High performers exit an organisation more often than low-performers, and if so, what leads to that turnover? Data based insights can empower business leaders to take right decisions regarding talent rather than mulling over intuitions or finger pointing between HR and Business.

 Here are 6 big Benefits of HR Analytics

Improve HR alignment to Business Strategy

It is very common to see that HR function in isolation vis-a vis the business. If you don’t agree with me, find out what business leaders do when HR slides are put up in Management Committee presentations and what HR head does when Business slides are put up? Most HR metrics, processes, & policies are benchmarked with respect to industry and competition, but very rarely they are aligned to hard hitting reality of their own business. For example, just by aligning HR metrics to business metrics, such as HR Cost per Revenue or HR Cost per unit sold, Revenue per employee, Average Lead time to productivity, HR professionals can take the first step towards better alignment to business strategy.

Complex decisions regarding the hiring, employee performance, career progression, internal movements, etc have direct impact on business strategy. When HR Analytics can provide insights on which employee is most likely to be productive in a new role, who is most likely to accept a internal job movement based on historic data, how long is it likely to take to close a critical position, based on data, HR seamlessly aligns with Business needs and strategy.

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Creating meaningful HR Processes

Not long ago, HR was marred with policy paralysis. Organizations had HR policies for everything. Processes were built for those policies and not for people who would use, manage or benefit from it. HR Automation is many ways has helped organizations their standardize processes. Whether it’s about Leave Approval, Employee Escalations, Reimbursements, Payroll, etc.

When we have meaningful data that provide us insights about processes, we will be able to take decisions that matter the most for our employees. For example, an organization introduced flexible working hours for its executives just because everyone in the market is doing that. And because few employees asked for it. Few weeks into the few flexi working system, surprisingly, they found that most employees wouldn’t avail this benefit. Data suggested that 90% of employees commute to work using company shuttle as the organization is located in an industrial suburb. So just by looking into data, organizations can build processes that are meaningful rather than what is an industry norm. 

Another popular example is that of Google reducing the number of rounds of interviews based on data, thereby improving candidate experience, interviewer experience and cutting down on the lead time to hire.

Enhance Employee Experience

Insights from the data across employee lifecycle can help HR managers emotionally connect with employees, build personalization , etc., For example, if an employee struggles to comply with certain HR policies, data of can provide timely insights on how the organization can support the employee in bettering his experience during the tenure thereby creating a win-win situation.

Improve HR Effectiveness

Data insights from HR analytics can suggest to us which candidates are likely to get selected, which are likely to perform well, if selected, thereby enabling the business to increase its performance and success rate. Such insights can be used in not only hiring, but in career progression, retention, learning and development, etc., For example, it would be an invaluable insight if HR can suggest which employees are likely to perform together without conflict, if business wants a put a new team together.

Reduce HR related costs

HR Analytics can help HR managers identify blind spots as far as leakage is concerned. For example, how much increment should we give a candidate, what are the increment slabs that the organization have so as to keep employee attrition within certain level, and so on.

Build a Great Place to Work

Ultimately, it is every HR head’s dream to build an organization that employee’s love to work for -One where employees wake up every morning and say, ‘here’s another great day’. Instead of being a copy cat and experimenting with what works for other best employers in your industry or country, delving into data can cull out insights on what your employees love, relish and dislike.

Nilakantasrinivasan J

#nilakantasrinivasan-j #canopus-business-management-group #B2B-client-centric-growth #HR-analytics #big-data #HR-metrics

Is there a difference between Six Sigma and Lean Six Sigma?

Lean and Six Sigma are close cousins in the process improvement world and they have lot of commonalities. Now we will talk about the difference between Six Sigma and Lean Six Sigma.

Six Sigma uses a data centric analytical approach to problem solving and process improvements.  That means, there would be time and effort in data collection and analysis. While this sounds very logical to any problem solving approach, there can be practical challenges.

For example, some times we may need data and analysis to be even prove the obvious. That is lame.

On the other hand, Lean Six Sigma brings in some of the principles of Lean. Lean is largely a pragmatic and prescriptive approach. Which implies that we will look at data and practically validate that problem and move on to prescriptive solutions.

Thus combining Lean with Six Sigma, helps in reducing the time and effort needed to analyze or improve a situation. Lean will bring in a set of solutions that are tried and tested for a situation. For example, if you have high inventory, that Lean would suggest you to implement Kanban.

Lean is appealing because most often it simplifies the situation and that may not be always true with Six Sigma.  However the flip side to Lean is that if the system have been improved several times and reached a certain level of performance and consistency, Lean can bring out any further improvement unless we approach the problem with Six Sigma lens, using extensive data collection and analysis.

Looking at the body of knowledge of Six Sigma and Lean Six Sigma, you will find that Lean Six Sigma courses following tools:

To learn Free Lean Six Sigma Primer Certificate Course
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To learn Green Belt Online Certification Course
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To learn Black Belt Online Certification Course
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Nilakantasrinivasan J

#nilakantasrinivasan-j #canopus-business-management-group #B2B-client-centric-growth #Lean-six-sigma #six-sigma-green-belt-certification #six-sigma-black-belt-certification

Background

An automobile manufacturer wanted to identify key independent measures (lead measures) which have to be improved to be successful in critical success factors of strategic initiatives across supply chain and manufacturing.

Solution
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