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Democratize Data

In a nutshell, democratizing data means that the business takes ownership of company data assets. Additionally, various roles will take the lead to determine what the data means and how it is used. This will also make it easier to determine the people who will have access to data they need and when they need it. Of course, security still plays a significant role for many business reasons. People need tools and training to visualize and interact with data to become data literate. They will need to cultivate skills to gain insights from data that can be turned into actions that pay off. Visualization software such as Microsoft’s Power BI, Tableau and many others have emerged to make this a real possibility to democratize data. The learning curve for visualization tools is very small and can help deliver insights almost immediately. With tools like this, the business is able to self-serve most of their data needs which creates additional capacity for your highly paid IT department and BI team members. Democratizing data also eliminates bottlenecks for decision making and empowers your people to achieve company goals. There are many benefits but the most meaningful may be in how it helps to create a truly data-driven culture.

The Black Market of Data

There is no shortage of people that believe data democratization can create more problems than it is worth. The thing is, various forms of data democratization has actually been living underground for years and is still alive and well. See if this sound familiar… Your sales group receives their end of the month report from the reporting team. The butchering begins! This beautiful pristine report is dumped in the meat grinder we call excel.  More data is stitched in from manually tracked excel spreadsheets. Custom calculations and formulas are sewn together. Other departments like Marketing and Accounting trade numbers to get their own metrics worked out. like a witch stirring a bubbling cauldron, sales adds a pinch more of this and a pinch more of that. Gurgle-gurgle-pop! A new report is born! All done under the radar, your project managers and BI teams are blissfully unaware who is already actually providing the analytics that is driving the organization.

Some Best Practices

Best practices and perspectives to look for when democratizing your data. There are others but these are some of the heavy hitters.

• Business is in the driver seat and IT rides shotgun. Everyone is in the bus together
• Everyone has access to data that is relevant to each role
• Everyone receives important security training
• Data governance program is alive and well with active participants who have ownership of their data and processes
• Business creates their own visualizations and IT/BI teams support through training and help when needed
• As a general rule, the IT/BI team spends time works 80% on core responsibilities like data models and back end dev. 10% complex reports for business and 10% coaching business on self-service.

Other Thoughts

There is plenty of specifics that would need to be worked through depending on the unique challenges of each organization. This simple blog post is by no means an exhaustive guide but hopefully it provides a general idea of what to shoot for on the journey toward a democratized environment. The important thing to remember here is that the business must play the lead role when it comes to data. After all, they are the ones on the front lines getting it done.

 

The PERFECT Feedback Loop

Feedback loops are your friend when it comes to establishing a culture of growth in your company. The perfect feedback loop is a model based on the tried and true scientific method and has been geared for growth when it comes to business. It is for anyone in an organization that has a problem and needs to find a solution to it. That means everyone can use it!

P.E.R.F.E.C.T

Problem – You observe something off. Maybe you see some strange outliers in reports. You know something doesn’t look right. Maybe you need to find the answer to a burning question. Perhaps you need to get measured improvement in a process? What other problems is this causing? Whatever the problem you have identified is, Be specific and understand it completely.

Explore – Gather data and visualize it. Make observations. Find existing knowledge through research. What are the facts that matter to the problem? Get peoples opinions and experiences through focus groups if it makes sense. Consider surveys that can quantify sentiment or opinion.

Reason – Use your reasoning to explain the problem. Come up with solutions based on what you know from exploration and research. What you come up with may be a no-brainer and can be put into place very easily. You might find that the best solution is already in place and that is fine too. Continue on the process when you need to get buy in from others.

Fact-Find – Test your solutions that you came up with. If you were wrong in your assumptions then a failure brings new information to light that can be built on. Thomas Edison famously said “I have not failed, I’ve just found 10,000 ways that won’t work”. This is where you deal with the burden of proof. Work hard to make sure you have tested enough to feel comfortable that your facts are accounted for with real data and successful tests.

Establish – Bring it all together and make your recommendations for action. At this point you should have some valuable knowledge that can change things for the better. This step will prepare you for all the concerns and objections that might otherwise bury your findings. Keep in mind that Initiatives get scrapped for all sorts of reasons such as politics, funding, risk, lack of buy-in just to name a few. Get your ducks in a row and be prepared for objections.

Communicate – Get the story out there. Tell everyone about the attempts, successes, failures and journey that got you the right answer. Stories have been a part of our evolution. Focus on your audience and connect with them. Get buy-in and support for your solution. Even if the solution does not get implemented, you are still bringing valuable information that may get others to make different decisions.

Trial – Hopefully you were able to get the support you needed and got your idea implemented. Now you want to use data to keep an eye on it. Is it working like you expected? Are there new unexpected problems? Are there new opportunities that have presented themselves? If things are looking good then great! if not, start the whole process over again with a new problem.

This model is amazing when it comes to growing your business with continual improvement. Give it a whirl on your next project or problem to bring the best solutions forward.

Pick Smart KPI

Key Performance Indicators are important metrics with one little difference, a title. Metrics get promoted to the status of KPI when they become a point of focus to help achieve an organization’s strategy. It is a powerful tool for communicating what is important for all aspects of an organization. KPI is also a change management tool to get buy in and build habits.

P.I.C.K

Positive – Only consider metrics that count toward winning a strategic objective of the business. It can be tempting to considering numbers that are just measuring problems or errors. However, those are best left for analysis and quality control.

Immediate: Go for real time data when it comes to KPI. If you don’t have the system capabilities then daily will work but don’t settle for less. A key performance indicator should be watched, talked about and acted upon to achieve results.

Certain: Everyone needs to be able to trust the data. Once you see a number, you can be sure it is correct. Metrics that are systematically stable are better choices as they are more trusted as the process to generate the data is standard.

Know-how: Have a plan for your KPI beyond just hitting a goal. Use them to help understand your organization so that you can help it grow. Ask yourself questions like: What does the metric represent and mean to the team or company? What will need to happen if the number is too low or too high? Make sure metrics that are promoted to KPI connect directly to company strategies.

S.M.A.R.T

Simple: People only care about things they understand. Therefore, KPI must be easily understood. Being specific can go a long way in helping to achieve simplicity. Additionally, make sure to always limit metrics that you crown as KPI around 6 to 8 at any given time. A big mistake people make when it comes to KPI is having too many of them. This is self-defeating since nothing can be important when everything already is. Use focus to drown out the noise and hit the important things.

Measurable: You can’t manage what you can’t measure. Quantitative metrics are always the best choice here. Qualitative metrics represent opinions and classifications that are usually better left for support and analysis. Fun fact, qualitative metrics are not actually considered a measure.

Actionable: The subject being measured should have direct impact on the numbers. Feedback will be useful in changing processes that can yield better results.

Results-based: One of the main purposes for KPI are to measure results. Example, if you have ever spent any time in sales you have likely heard that “sales is just a numbers game. For every 9 no’s there is 1 yes. Therefore, more calls will make more sales. Let’s make outbound calls our KPI!” Sounds like a great idea but measuring tactics like this have limited growth potential. Instead, measure how many deals are getting closed. This sends a clear message that sales getting closed is what is most important. Inspire and empower your people to be resourceful.

Temporary: Give your KPI an expiration date. Business changes and strategies shift. Busy seasons and growth can dramatically raise importance of certain metrics. Try to time them and find cycles that go with the ebb and flow of your business. Aim to have KPI reviewed and switched up monthly or quarterly. You want it long enough that you can build habits and implement changes.

KPI Overview

It can be very difficult to find KPI that is perfect and covers everything mentioned above. You may find yourself needing to pick KPI that is just good enough. Lastly, Make sure your KPI is not used for incentives or discipline. This will corrupt your data as it motivates people in finding ways to game your systems. Now that you know what it means to pick smart KPI, use what you have learned for the next goal setting or strategic planning meeting.

You see this pyramid all over the place when people start talking data. The DIKW model has been a part of information sciences for many years. Also known as the data-information-knowledge-wisdom hierarchy and associated with knowledge management. It lays out the relationship for how data gets meaning through the lens of our perceptions. Although it is unclear who exactly came up with the concept, many different people have referenced the concepts throughout history. To describe it better, One way to show the relationships might be the English language and how it uses the whole hierarchy to communicate meaning.

Data

For our example, the English language contains words made up from letters which does not really mean a whole lot by themselves but they serve as the base to build the next steps of meaning. This is much like how data provides the building blocks of information. On a side note, it is very important that data is consistent in order to be useful. if people had different interpretations for what vowels were, we would be in a real pickle.

Information

Onward with our analogy! Sentences provide meaning for groups of words and is a good example of the relationship information has with raw data. Although sentences by themselves are still pretty neutral, they are very important to forming concepts and describing the world around us which become our knowledge. Information is like a sentence and describes a complete thought.

Knowledge

Paragraphs give meaning to groups of sentences and paint the picture of points that are made. At this level we use logic and reasoning to calculate answers to questions. Knowledge also deals in deduction and is able to build on itself from just a couple key sources of information. At this level, we also categorize information to be true or false.

Wisdom

Books are like wisdom and give us the whole story with the big picture. They are made up paragraphs and chapters that build off of each other. We learn the moral of the tail along with full lessons that enrich our existence while making life a whole lot easier when we know what to do and how to do it.

Our lives are like vast libraries which contain books that represent our experiences. We use wisdom to give weight to things we value which helps us to make the best decisions possible. Combinations of Data, information, knowledge and wisdom we trust ultimately turns into the actions we take which determines outcomes of success or failure.

This model gives a great simplified look at how information comes together to create knowledge and wisdom. The DIKW model can turn into a very deep conversation as we start throwing other things like right and wrong or morality into the mix. With all this in mind, how does knowing the relationship of data to decision help you?