Data Based Mindsets – Maturity Levels
As of 2021, organizations have heavily invested in data infrastructure and supporting resources. But it’s grim to hear that nearly 85% of all data and analytics based transformation projects fail to meet their objectives.
There can be a long list of reasons for this state of affairs, but an undeniable contributor and a systematic issue is the organization’s culture – A lack of a Culture of Data Based Mindset.
Many times when we don’t know what is the problem with the organization, we tend to brand it as a cultural issue. So to say, the problem is attributed to Data Based Culture or lack of it, is a biased statement without going deeper into the issue.
The willingness of employees to accept & adapt to the new way of working. ie., taking decisions or actions based on data, is in fact the real barrier and reason for low adoption of data based transformation projects.
This is one of the new pillars of professional excellence – being fluent with data and making it an integral part of day to day actions.
Data Fluency, Data Literacy, Data based Mindset – whatever name we want to give, it boils down to how comfortable we are with data.
Like any other new technology – mobile, web applications, smart devices, social media, etc., we have a continuum of users of different maturity and proficiency in Data Based Mindset or Data Literacy too
If you wish to honestly self-assess or evaluate your team on where they stand when it comes to using data for decision making, a Data Based Mindset Maturity Model that covers data literacy maturity levels such as the one below will be very helpful. We’ll now look into the levels of Data Based Mindsets:
Resist – confused beginners
At this level, at heart, an individual is a disbeliever in data based decision making. Such individuals would hardly look into data but when they do so, they try to run a variety of logical counter-arguments to discredit data and its insights. One can say that they have a strong belief system that is anti-data or facts, which is based on biases, preconceived ideas of the situation, hear-say facts, anecdotal evidence, etc. Folks at this level offer maximum resistance to change. At the deepest level, it can be on account of fear of some kind. When an organization has many key stakeholders and king-pins in this bucket, the organization would more or less be a data-laggard. Ultimately they will have to take off from this level due to peer pressure and so ‘confused beginners’ is a fitting description for this group.
Access – social drinkers
At this second level, individuals are limited users of data, only based on necessity. I’m tempted to compare them with ‘social drinkers’. Situations and environment forces them to consider data and they do so with reluctance. Naturally, they are users with limited proficiency in data handling and are uncomfortable when placed in data rich discussions.
User – consumers and cheerleaders
Bulk of employees in organizations that are doing well today, fall into this group. They believe in data based decisions. So there is no mental block with this group. But they have skill limitations. I’m tempted to compare them with the audience and cheerleaders in a football match. They love the game, they enjoy and relish talking about it in great detail but they’ll always be in the stands and never put their foot on the playground. Either they don’t have the skill to play or they are too old or not physically fit for the sport. But being here is not that bad from an organization’s perspective. They are willing to consume data and inferences given to them and believe in it.
Understand – power users
They are individuals who have good expertise and are strong believers in data. They lead with data, whether it is about analysis, framing scenarios, statistical and probabilistic analysis, considering divergent views from data, they are very proficient. You can take them as ‘power users’. At extreme, they may tend to be ‘annoying experts’ too :-).
Create – prosumer
Standing at the highest maturity, this group may not be really senior in organizational hierarchy, but they definitely are good at synthesizing deep insights from data, applying unconventional & innovative methods to generate unique value propositions for business and customers that can disrupt the current state. They look through the data beyond the obvious. You can call them the ‘prosumer’. They are both the producers of insights and its consumers. As a result, they are the trend setters. Obviously there are going to be only a few fitting into this group.
This understanding of the Data Based Mindsets & Maturity Levels can be applied to evaluate its relevance to your industry, specific roles & departments and their ideal maturity states, skills needed and critical mass needed at each level to build a Data Based Mindset Culture, etc.
If you wish to learn more about evaluating your organization on Data Based Mindsets & Maturity Levels or create a roadmap, feel free to contact us.
10 Reasons why sales teams are reluctant to embrace sales analytics
Well, everyone knows about the importance of analytics. Many sales professionals sell ‘Analytics and BI’ products and services, yet they fail to embrace it. It’s quite surprising that they recognize its importance, its relevance to their growth and survival, but don’t get into action.
If you are a Sales Director or Sales Manager, have you ever wondered why this negligence?
Here are top 10 reasons for this reluctance:
1. Data is not available
The first and foremost reason that Sales Managers give is that they don’t have ‘those’ types of data in Sales. It’s difficult to collect – partners don’t cooperate, systems don’t have functionality to capture, it is not important in our business, etc. This is a show stopper.
2. Data is not readily usable
Data provided has many empty fields, some times even incorrect, only some partners or clients share information, etc., and so it’s not possible to use this data to perform Sales Analytics. Cleaning the data is time consuming and Sales Managers feel they don’t have resources to do it.
3. Not able to go beyond plotting the charts
Many Sales Managers are proficient enough in excel to plot some basic charts. But they are unable to go beyond. The challenge is that sales organization has been traditionally ignored when it comes to analytics related upskilling of talent.
4. Don’t know what analysis to perform
Many times, it is important to frame the problem and look at the data to identify the reasons for the problem. Sometimes, it’s exactly the reverse – Look at the data to even define the problem. So a structured problem solving approach is needed by Sales Managers and many of them aren’t’ skilled in that.
5. Not able to link analysis outcomes to ground reality
Some of them, especially the Sales Analysts, are able to perform good quality analysis, but no matter how good they are in sales analytics, one question is never answered – Why is a particular phenomenon occurring? The answer to this question will only come by linking the analysis to field observations. Unfortunately, when the analysis doesn’t provide anything useful, teams loose interest.
6. Not be able to convince stakeholders with the data analysis
Many Sales Managers find it easy to allow the Sales Directors to lead the conversation, lead the analysis and direct them on what actions have to be taken. Proactively analyzing the data comes with the risk of defending the analysis and insights, so identified. Sometimes it’s going to make them unpopular among their bosses. So it is understandable that there is a natural resistance to it. But another way to see it as a lack of storytelling skills based on Data Analytics.
7. No one is asking for it
Organizations that are laggards in Sales Analytics still work the traditional way. Their Business Development Head, Sales Directors, & Senior Managers aren’t data savvy and prefer to manage sales without much use of data and sales analytics. In such organizations, sales managers who rely on sales analytics will sooner or later be left with no motivation to pursue it.
8. It is time consuming and that time is better spent in the field
Analytics is a skill and any skill needs practice, if one wishes to master it. In the initial stages, lower proficiency means more time in learning. Many Sales Managers are restless and feel it’s a mere waste of time and energy to crunch numbers and look for insights, especially when action is happening out there in the field!
9. Able to meet targets without such analytics
Some sectors and organizations are lucky to be in the sweet spot. Their products and services have high demand and less supply. But history suggests that this is only a momentary state. Disruption happens everywhere, no industry or organization is spared. If not today, for tomorrow’s survival, sales managers need to upskill in Sales Analytics and learn to adapt. Failing to do so is mere complacency.
10. Company already has CRM
This is probably the most common explanation we hear from Sales Managers. Sales Analytics is a skill not a software tool. Traditional CRMs were only a workflow system carrying a repository of sales data but many of them have now acquired BI and analytics capabilities. But, general purpose inbuilt charts and analytics, may or may not address the problem of a particular territory or scenario. So effective Sales Managers do leverage the Sales Analytics from CRM and other sales enablement tools, but they make a point to apply their own sales analytics skills, over and above that to alleviate their problems.
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)
- Data Quality & Data Governance
- Conviction of Sales Leadership towards data based selling
- Sales Analytics Talent & Capabilities
- Cross-functional Alignment
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.
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.
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.
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..
Sign-up for collaborat newsletter