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.
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..
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