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One of the pillars of an exemplary data management and governance program is data literacy. Organizations often assume that their executives or data users are not data literate and don’t understand how to ensure data is of quality and how everyone has a role in creating and managing data. Internal branding about how data helps management make better decisions has been around for a decade. But to go from data to information and knowledge, data literacy is not enough for the clients of data analytics practitioners. Business data analytics users need accurate multi-disciplinary skills to ask themselves what the data tells us and where and how these insights can be applied.
Some firms will launch a simple branding campaign that says, “What does the data tell us?” or “Listen to the data.” While doing something is better than nothing, we would like to think rightfully or wrongly so that in 2022 most organizations are beyond this approach.
In this post, I posit that data literacy programs need a bit of a reset, given the current point of view on data literacy existed coming out of the age of business intelligence. In the age of AI, self-service analytics, and digital customer experience, what goes into a data literacy program needs to be reset, and the view of what users know about data and analytics needs to be reframed.
The Data Literacy Programs Of Yesteryear And Many Still Contain…
A curriculum that starts with, well, data is the currency of the times. It is the oil or glue that holds an organization together. Therefore, it is a strategic asset we must ensure is of quality, well-curated, and created correctly. These programs will then show how data is made, hopefully with examples/use cases from their business.
For instance, they will give a flow diagram of a customer service representative onboarding a customer and creating the initial customer record to show how an account should be set up and what happens if incorrect information is entered, or if the information is not filled in and left incomplete what that does to the ability to market and communicate with the customer.
This reminds me of Saturday morning cartoons I watched as a kid, where we learned about how a bill becomes a law. “I am only a bill sitting on capitol hill.” While this is a valid use case from talking with business stakeholders, it borders on insulting as most people in their consumer life are engaging with a virtual assistant such as Alexa, wearing a smartwatch or tracking device such as an Apple Watch or a Fitbit, and using apps or other tools in their daily lives. Algorithms are everywhere, and people know them, and businesspeople know them as well. They understand what data is and how it drives consumer interactions. Many business stakeholders use operational dashboards and other data visualizations to run their businesses or departments. So, if we are ever to get into the world of insights to action and adaptive intelligence that industry researchers discuss, we need to go much further than using account setup examples. New examples such as how data analytics powers the guidance and advice advisors in a firm give customers through insight. Or how recommendation engines power next best actions which are sent to digital applications in real time are more modern relevant data analytics examples.
So, the time has come to rebrand data literacy, data analytics literacy so we can get more signals and patterns from the data we are collecting and move into improved decision-making.
So, What Is The Data Analytics Literacy Curriculum Of The Future Then?
I recommend that in the spirit of test and learn and lean start-up/design thinking; the firm develops a vehicle to assess what their audience knows: briefly, whether that is a survey and focus group or playing a fun game (like jeopardy or other skill-based assessment) to assess the knowledge and maturity level that can help you develop a new curriculum.
Using the outcome of the assessment above combined with the five critical focus areas I am proposing below can help set the stage for a world-class modern data analytics literacy program. The program could include:
1. Data Fundamentals: What are the components of master data management? Quality, governed, gold standard data. This includes a description of the business benefits of governing data and clearly explains the importance of domains such as lineage, business definitions, and the data catalog.
2. How Data Turns into Information and Knowledge. What platforms are required, and why do business users need to understand these fit-for-purpose platforms?
a. What are the benefits of cloud-based platforms, data lakes, or lake houses, and what data science workbenches do, as well as self-service analytics, and why are these tools important? Why should the firm invest in these?
b. Business users should appreciate data Infrastructure-as-a-Service and managed cloud data warehouse such as Snowflake and what they can do to improve end-user access and protect privacy. What is the difference between structured and unstructured data and how data models and platforms may be different depending on the data structure in question?
c. Digital, Marketing Automation, and CRM Fundamentals and Platforms. An appreciation of real-time decisioning and omnichannel customer engagement including how data analytics informs customer conversations, lead targeting and qualification, and overall knowing the customer.
3. Lean Start-Up and Design Thinking. Fundamentals of design thinking, test and learn, control groups, and how to measure the success of testsâquantitative and quantitative research. Why is it essential to create a baseline, and how do you set up good KPIs to improve performance?
4. Analytics Fundamentals. Starting with the importance of defining what business problem you are trying to solve and then moving to select the proper analytics methodologies. Go to market analytics, segmentation, and a basic overview of the types of analytics, from descriptive to predictive. Program-related analytics and measurement, customer lifetime value, and engagement. As a consumer of analytics, the businessperson should have a basic understanding of how specific analytics solve business problems. Depending on the firm and industry the types of potential analytics should be listed and explained in the context of potential application to help solve business problems. For example, if you are in a digital business, digital analytics and digital signals to sales and how you measure SEM/SEO should be discussed. If you are in a retail business, site placement and drive time analytics should be reviewed. If you are managing risk, transaction scoring and analysis using deep learning should be reviewed. If you are in a large consumer business with lots of cross-selling, various marketing analytics should be reviewed. Consider establishing a baseline through certifications such as INFORMS CAP.
5. AI and Data Science Fundamentals. Explain the difference between how statisticians think versus data scientists. How does machine learning enable AI applications? The types of AI and how to work with data scientists. What are good questions for data scientists when building statistically oriented products and services for you? How do you know the model or tool is good and working correctly? What are the various types of models that can be built and what do they solve?
Given we are now in 2022, it is time to upskill and move to data analytics literacy. I recommend that some type of handbook be developed for the above and the course also be available through video training and updated at least annually. Also, consider a modular approach to the curriculum design where you define the categories and then can keep adding topics and use cases. This program is a dynamic living breathing program and not a point-in-time project.
In summary, these five areas will help business users of data analytics drive more impact with insights through understanding what is possible with the applications and use cases of data analytics. These five areas are not the only ones, and I would like to hear from the readers of this newsletter about what domains or subjects could be added to this curriculum.
I look forward to hearing your thoughts on whether the time for this reset has come in the way data literacy programs are approached. Also please share any success stories or changes you are seeing in the marketplace. What has your experience been with these programs? Are you using any third parties or consultants to set these up? What role do HR and internal education teams play in designing and enabling these curricula
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Disagreeing with other people, without taking a body count or courting disaster, is something most people try to avoid. Nevertheless, we recognize we can’t always agree with everything that comes our wayâeven if it comes from the boss.
Many of us think disagreeing with the boss is one of those career-limiting moves to be avoided at all costs. Think again. Most managers want to think they’ve hired brilliant people who can think and act well on the company’s behalf. That includes not letting them (or anyone else) drive off a metaphorical cliff. This means you are being paid to use your brain AND mouth.
The diversity that takes place in the workplace isn’t just about race or religion; it’s about ideas, perspectives, and insight. If you are truly engaging in what is taking place at work, it’s not possible to agree with your boss 100% of the time.
You can disagree with your boss and make that disagreement a win-win for both of you. You can win because you can use it for career enhancement. The boss can win because they will come off as an engaging manager and get a much better end result.
Here are eight tips to turn disagreement into a great thing for your career.
1. Disagree, But Don’t Be Disagreeable
When something strikes you as wrong or out of line, keep your emotions in check. No one, especially the boss, will appreciate an emotionally charged rebuttal. People tend to mirror each other’s energy level, and if you turn red and flap your arms, it will be met with equal intensity.
2. Don’t Make It Personal
The conversation will go much better if you are addressing the issue or topic and not making your disagreement about the person, your boss.
3. Be Clear About What You Don’t Agree With
If you can’t articulate what is troubling you about something, wait until you can be clear. If you can’t be clear, you will not have a conversation that will make any sense to the other person. A confusing conversation will not leave a great impression.
4. Offer Alternatives
Nothing falls flatter than squashing an idea only to have nothing to replace it with. If you can’t think up a better idea, then what good is the disagreement? Sure, you might not like the idea, but if you can’t come up with something else, then go with what you have. You have to solve problems to be an asset.
5. Make Things Private
Depending on the setting and issue, you may need to take your disagreement to a private setting with your boss. This allows you to cover whatever you need to, have a discussion, and keep both of you looking good to the rest of the office.
You never want to embarrass your boss; if you do, they will remember it for much too long. They will appreciate your sensitivity and professionalism when you have the insight to know when it’s time to have a private discussion.
6. Seek To Understand
Many conflicts and disagreements are rooted in a failure to communicate and understand the other person. When something does arise that doesn’t hit you right, ask questions and gain clarity. You may discover that you do agree after all. Doing this will also help you avoid discomfort.
7. Don’t Be A “Yes” Person
This is more than simply sucking up to the boss. This is agreeing with the boss at the cost of your character, values, and career. You might think it will enhance your career, but it will backfire against you as the higher-ups see that your contributions are limited.
8. Disagree And Commit
The biggest issue that managers have when employees disagree is their becoming insubordinate and undermining efforts. If you have followed all of these steps and you still have a disagreement, then it’s time for you to disagree and commit yourself to whatever is being proposed. After all, the idea or direction might really work out well. Your manager will think you are truly a professional if you can work through your disagreement, offer solutions, and be able to “get on board.”
Certainly, out there in the universe are managers with fragile egos who can’t tolerate anyone disagreeing with their mandates or directions. They too will only get just so far in their career. Anytime you limit the free flow of thought and contribution, you limit the possibilities.
You need to screen for these people in your job search. If you wound up with a boss like that, you should consider a different team or job. But most managers enjoy discussion and debate as a means of developing great ideas and direction. They understand that disagreement is part of the process.
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This article was originally published at an earlier date.
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