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That DATA Thing # 5 | Diaper rash is still a thing?
We are all confident that betting on new technologies is the thing to do. We also have to keep our eyes on the road, take care of the essentials. Like changing diapers at regular intervals, we must also remember that the basics must be done and must be done well.
Here are two lists to help us ponder and contrast our activities
Things you must do:
Generate a Profit & Loss Statement
Monitor your inventory levels
Have Timely Aging reports
Magic we should expect:
Natural Language request & response
Document processing and matching
Auto-generated insights
You must determine your risk tolerance and allocate your resources accordingly between foundational and cutting edge disciplines. Keep enough focus on the proven basics in order to fund your riskier high-potential data investments.
People will listen to your crazy ideas when you can show you already excel at the essentials.
Diaper rash IS still a thing.
That Data Thing #2
Is SELF-SERVICE analysis & reporting always a good thing? The potential is immense—almost unstoppable. It can:
empower pride of ownership
foster self-initiative
require minimal supervision
often regulates itself
When done right, the author:
is a subject matter expert
masters data transformation
excels at visual presentation
holds credibility within the organization
However, the risks include:
dependence on tribal knowledge,
a single point of failure,
limited distribution, and
faulty logic
So, when is it okay to "crash the party"? Can we govern the ungovernable?
That Data Thing #1
Data Capture
Large Data volumes
Data Storage Capacity
Analytic Query Performance
Building resilient semantic models
Integrating Multiple disparate Data Sources
Choosing and deploying a future-proof technology stack.
Keep my stakeholder’s attention span so that they understand that what they are asking for, while right on target will take some effort and several iterations, specifically their time and commitment to validate that the results are correct and addressing their needs, even if they do not know how to explain it in a manner that is comprehensible let alone executable.
Which item should I focus on?
My capability to synthetically express complex technical challenges?
Educate the business stakeholder on Data Practices?
Is your organization facing any of these big challenges? Let’s start a conversation…
That Data Thing #1
Artificial Intelligence
Modern Data Platform
Operational Data Store
Data Mesh
Data Fabric
Data Warehouse
Data Lake
Data Lakehouse
Data Hub
Why do we gravitate to a single concept and try to make it fit our situation? Here is the process: Evaluate the best option from the list, choose the “best” one, request a bid to get it done. What could possibly be wrong with getting the best thing for the best price? It's unquestionable, rock solid.
Answer: we are uncomfortable with complexities and need short taglines that our stakeholders can attach to - if anything, emotionally. Yes, we need to admit that decisions and commitments will always have a strong emotional component.
So, present the above list to your board, share a FOMO triggering quote, show them a cute puppy picture, tell them you need a budget for artificial intelligence, you will always get approval. How much? You’d be surprised!
So forget your scientific approach to data informed business performance. Help your stakeholders feel better by giving them what makes them feel good. Yes, it must be expensive. Spend your budget slowly and produce clever quarterly status reports. When buy-in starts to wane, start hinting about a new paradigm shifting trend that... you guessed, needs a “research budget”.
Hot Tips for a Successful Data & Insights Program #6
You can do it! A trusted partner can help.What are your thoughts about DIY? Love it? Hate it? Or somewhere in between? Yes, it is never an on/off, black or white decision.
Some of us find our happy place firing off a bidding war for a turn-key project and leaving no stone unturned. Do you just want to see the thing finished? Or do you have a list of cool tools you want to get, and the only thing you need is an excuse project?
When it comes to DATA, start by identifying who you are as an organization. Are you happy being the Master of Ceremonies or dabbling into specifics? Can your organization fund, fill, and maintain a complete skill set?
From functional expertise, through Data Governance, Data Modeling, Semantic curating, Visual Presentation, and Interactivity – every skill is needed for success. Not that easy. Most likely, your team will have some weak areas and others where strength is obvious. Take this clue and find the right partner to fill in the gaps.
Reach out for help where it makes sense and keep in mind that some roles are not needed in all phases of your project. Know the roles you need and map them to your strengths. Identify intermittent needs and build a known network ahead of time.
Most importantly, start by seeking, engaging, and securing expert advice. Turn to this objective and trusted advisor at each turn in your journey. Now you find yourself smiling; your roadmap no longer scares you.
Hot Tips for a Successful Data & Insights Program #5
We prepare DATA with the aim of influencing individuals with the power to make a difference - this is our AUDIENCE. While sometimes data triggers actions automatically, most of the time it's meant to influence a person. Your audience could be enforcers, investigators, or even everyday passersby.
A DATA program can't guarantee how it will affect each profile, but understanding them can help prevent mistakes and improve your success rate. Gathering feedback from your AUDIENCE and debriefing after interactions is crucial.
The misconception that live data is always necessary should be debunked with timely updates and delivery. The pace at which your organization makes decisions should guide your DATA processing frequency. For instance, if your subject DATA is for quarterly sales targets and bonus analysis, updating it monthly might suffice. On the other hand, if manufacturing orders come in daily, triage data should be updated hourly or even several times a day.
Understanding your analysis and decision process helps design an efficient DATA processing cycle, determining the necessary speed and capacity.
Hot Tips for a Successful Data & Insights Program #4
Dimensional Attributes are vital in data programs. They help us make sense of data by providing a structured framework. Think of them as the key characteristics that bring clarity to your information.
Imagine dimensions as the familiar three: height, width, and
depth. We grasp these effortlessly. Time is another dimension, essential but different. For instance, think about the last time you saw your carry-on bag, a moment in time linked to your experience.
Now, consider other attributes like color, zippers, or wheels on
your bag. While these are clear attributes, they may not be crucial to airlines. However, they matter to you as they help spot your bag on the conveyor belt.
Dimensional attributes are like common markers that must be captured and can be critical for analysis. They enable us to organize, filter, and understand data.
Traditionally, we select and define these attributes upfront to
structure data and support analysis. Today's technology allows more flexibility, but a set of agreed-upon common attributes is essential.
Sometimes, these foundational attributes span multiple datasets, like unique identifiers for a location. "Conforming" them means giving them a unique identifier and identifying which Dimensional Attributes differ across data sets.
It might sound mundane, but when you lose your carry-on, having standard attributes can save the day, determining how long you can survive with just one change of clothes. So, managing Dimensional Attributes isn't boring; it's practical and indispensable.
Hot Tips for a Successful Data & Insights Program #3
Identify the Decision Makers. The first step is identifying who makes the decisions and how they reach those decisions. Make a list and compose a profile of their personas. Which are their preferences, are they comfortable, hands-on analysts or do they expect a presented brief? Do they consume insights or participate in generating them? This information is key to identifying the delivery method and the required user interactions.
Causality and Accountability. Every organization has attributes that show what caused a behavior or activity as well as who is accountable for it. These attributes need to be discovered, identified, and mapped across data sets. A Date, a Region, a Channel, Department, Product, Market, etc. will allow grouping and segmentation of data and enable conclusions. This is essential for both Data Governance and Analytics.
Decision Frequency. Organizations may formalize a review process, triggering accountability for performance against metrics. This process can be aligned with periodic meetings and typically aligned with the publishing of financial results. The analysis activity takes time, inside which the data set should not change. Data processing should be fast enough to support multiple analysis cycles that yield results in time for the review session. Identifying this cadence will define the freshness of data required.
Process cycle. The decision process must not be confused with data processing. A decision cycle begins with Data Processing, continues with Analysis, generation of Insights, Review, and Prescription. Formalize this process to align expectations but also to evaluate if skills and capacity are adequate.
Tracking and Monitoring. A prescription is materialized into one or more actions. The actions must be monitored, specifically to provide feedback as to their success and to provide validity to the Analytics and Decision process. The impact of actions must display evidence of progress towards success.
Insight Impact. An initial Analysis and Decision process may be empirical. It is important to prune and focus over time. You will prune topics of analysis that are not yielding insights and insight paths that generate sterile prescriptions. Over time, you will measure the effectiveness of the Decision and Analysis process to maximize the yield of the whole process. The Decision and Analysis process has a cost. It is on us to ensure the effort is worth it.
Hot Tips for a Successful Data & Insights Program #2
Make your success measurable. You know where you are going, but how do you know when you have arrived? How do you make your Data talk the same language as your success statement?
Are we there yet? We need to describe success in Data terms. We do this by defining a metric. A metric uses a number to describe your progress towards success quantitatively.
Metrics are ingredients. You can use a metric to help you describe a specific activity, but likely you will need several metrics that working together, help you describe your state in terms of success. A key metric is often supported by other metrics that inform the key metric.
Human Intelligence. Did you mean artificial…? Nope. People that are active in an organization have a pretty good sense of its health. Metrics simply help quantify certain aspects to provide credibility.
Self-governed. Many activities have their own intrinsic limits. To determine your bowling score, you do not need to know the precise trajectory nor speed of the ball. The track, gutters and foul lines provide a framework that governs the competition. You just need to count how many pins remain standing.
Key metrics. Choose the minimum number of metrics that you need to confirm your evaluation. You will then wrangle Data to produce and track these metrics.
Hot Tips for a Successful Data & Insights Program #1
Duh! Yes, but many times, initiatives start by selecting the right person or selecting the right technology. Better approaches start by identifying stakeholders and project methodology. These alone will consume significant resources and increase the chances of failure by distraction. Can they be ignored? No! But, they do need to fall into their rightful place. So where do we start?
Write your problem statement. Doggedly force yourself to compose your problem statement. Involve others, show them your draft, take their input. Ask questions!! The output must accurately and clearly describe the challenge but refrain from any form of action or solution. Just state the facts.
Success. Finish this process by writing a paragraph that describes the expected state. Explain succinctly but precisely what things should look like when you are all done. Use expressions that depict minimized efforts, maximized benefits, improved performance and desired results.
All done? Well, no you have just started, but… you know where you are starting from and where you want to end. These are the bookends, essential and obvious, but often overlooked.
More to come. Let’s start a conversation…
Hold on! Is it really all about the DATA, like they say data is the new oil? Well, I've got some news that might shake things up!
We often find comfort in simplifying complex concepts, reducing them to easy substitutes. Our minds excel at taking discrete inputs and transforming them into intricate facts that swiftly become decisions, then actions. This approach works wonders when our input devices are hard-wired to our brains and when our physical capabilities can execute all our actions.
But now, let's step into today's world. The number of available inputs is mind-boggling, growing exponentially even as you catch some shut-eye. The truly astonishing part? You might be missing out!
The journey from input to action has become a colossal undertaking – but is it even attainable? Like oil, DATA requires extraction, processing, control, and delivery. But unlike oil, our current focus on DATA seems to lean more towards effectiveness than efficiency.
As we seek alternatives to oil in today's world, it's evident that our primary concerns revolve around transportation, heating, and numerous byproducts, rather than oil itself. So, what are the byproducts of DATA? Can we consider business performance, safety, health, and overall well-being, just to get the list started?
So, it's not merely about DATA. It's about what you can enable others to achieve, how you can contribute to their growth. Let DATA empower you to be a hero.
There's plenty more to delve into here. Share your thoughts, and let's dive into a lively discussion!