Does your organization attract talented people ?
Does your organization put its people’s talents to work ?
Do talented people get more talented when they work in your organization ?
Do all the people in your organization get to exercise their talents when they work ?
Is your organization glad to see its talented people move on to other organizations that will value and reward them ?
Does working with your organization bring out the talents of the people in other organizations ?
Does your organization support its talented people when they chose to go back to the “beginner” stage and acquire new talents?
The need to improve your organization’s data culture is driven by the powerful new tools for data that are becoming available and the new strategies that they make possible.
In the frenzy over powerful new tools it’s good not to forget the most powerful “intelligence” tool that your organization possesses, its “Human Intelligence”. An organization’s Human Intelligence is determined by its skills, training and ability to adapt to changing circumstances. Such an ability is grounded on its member’s enthusiasm, trust and willingness to trust.
Tools cannot be used effectively unless they are grounded in the organization’s human intelligence. Sometimes, without the proper training, experience and enthusiasm to come to grips with a tool the tool can actually do harm to the organization.
Each time you introduce a new tool you should take the opportunity to review, rebuild and strengthen your organization’s human resources so that you can take full advantage of the tool’s capacities.
The most interesting result of Sodexo’s widespread adoption of QuickBase is not just the productivity boost but the increase in innovation, Bryant says.
“QuickBase is a low barrier to entry to try new things,” she said. “Experiments are not always successful so people can be reluctant to try if they know a failure will be costly.” —QuickBase Pushes Low-Code into the Enterprise
With a strong data culture the organization can trust employees to try new things, and when they work, to take full advantage of them. When they don’t work the employee is not blamed or punished, but encouraged to try again.
But Salesforce CEO Marc Benioff says that AI is … really the next big thing after mobile and social changed the tech world over the past five years.
Smart computers that can think, talk, reason, and predict will be able to do more than just search Google for us or order a pizza. They will eventually do stuff we haven’t even imagined yet.
Benioff, talking to analysts during Salesforce’s quarterly conference call, called this the “AI-first world.” –“Salesforce CEO Marc Benioff just made a bold prediction about the future of tech” in Business Insider
Salesforce is planning to add an AI component (called “Einstein”) to all of its platforms. Find out more here. Making use of such advanced data handling will require a data culture that is strong and robust and than can support its members in gaining new skills and insights.
We are going to see cars that “drive themselves” much sooner than anyone would have imagined. We will also see organizations that can “drive themselves” and make use of their ability to understand their environments and use data to drive their processes.
You may not be planning to use AI in your organization but you should be planning to strengthen your organization’s data culture to the point where you will be able to use it when you need it.
Start by establishing a basic training program and working to get everyone on board.
Think like Google: Produce a simple concept or idea as a beta, release it, and let users test it and give feedback. Then study the user responses and adapt the capabilities as you go. This kind of logic allows for a quick product release, less development dollars up front, and the opportunity to design the product based on consumer feedback. These initiatives yield successful results. It’s better to prototype a data product that is ready to put in front of a user in six weeks instead of six months. This allows you to keep it simple and make adjustments quickly based on what’s working and what’s not —“Putting People First in your Big Data Initiative” by Juice Analytics
This is the data-centered approach to change. Make your changes in small steps. Project what results you expect from each step. Test before and after the steps to check on your progress. If a step does not produce measurable results, modify your plan.
“Consumer feedback” is just one way of measuring the results of your changes. Most steps you take should also make some other impacts that you can measure. Making a data entry form simpler and easier to use should result in good consumer feedback, but it should also have other effects: fewer incomplete forms, fewer errors in filling out the form…etc. Often trying to figure out how you will measure the effects of the changes you are planning will give you new insights into just what you want to do, and how you should try to do it.
“Culture eats strategy for breakfast.” –Peter Drucker
Plans have to be executed. The minute an organization starts to execute a plan things will start to go wrong (or go right when the plan things they should go wrong).
The organization’s ability to adapt to the difficulties that happen when the plan is executed is central to its ability to execute any plan. An organization’s culture is what gives it the ability to overcome such unexpected events.
Think tortoise and the hare. Given the choice between having an organization with truly brilliant strategies, but with such a poor culture that it is unable to execute them and an organization with average (or even poor) strategies, but with the ability to execute them, most people would go for the later.
To make matters worse (or better, depending on how you look at it) part of a strong culture is being able to learn from its mistakes. One characteristic of a weak culture is that its ability to learn is also weak, so it keeps making the same mistakes over and over again.
To start thinking about your organization’s culture (in particular its data culture) you can take the Basic Diagnostic. Seven simple questions will give you some perspective on your organization’s attitude towards its data.