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Your first step towards Data Enablement

data enablement
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Prakash Baskar

February 9, 2021

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How do you clear the path for Data Enablement?

Data Enablement - It is something that is on the minds of many leaders and CEO's as they start to understand the power of data and analytics and more importantly what would happen to their business if they do not get it right - stagnation and failure are not an option. 

This article will be one of the most important piece of information you will come across, if you are onboarding a new leader to own and enable Data for your company. 

I do not know where we are in comparing data with many things around us - air, water, oil... the list goes on, but the fundamental idea is to use data more - creatively, across all areas of the company. For that to happen, you need to clear the clogs, blockages and set-up a system for promoting widespread use. 

You may build analytics, applications, API's, automation, AI or ML - those are all variants but the problem you are trying to solve is "How do I make my business or company become more efficient, faster, leaner, and stronger by enabling (using, leveraging) data across all that we do. 

When anyone speaks of Data Enablement it is about using Data across all the business areas, to do the following. 

  • Measure: How the business is doing across various functions and the critical metrics that I want to assess us on.
  • Monitor: Having measured, you want to monitor for spikes, changes, and ensure the results are headed in the intended direction
  • Manage: Take relevant and timely action and intervene as soon as possible and required before large-scale costly damage is done, or leverage the positive indications to do more of what is needed to move us ahead. 
  • Mitigate: When we do identify inherent risks or issues, how do I set-up processes, triggers and early warning systems in place that will help with adequate mistake proofing where needed. This helps with ensuring we do not make the same mistakes again and not do anything about it.
  • Multiply: The value of data comes only when the analytics and insights are applied. Today, use of data is not a must-do because we want to get ahead. If you don't do anything your business will not stagnate but move backwards. But intentional and diligent use of data and analytics, can help move the company forward, accelerate new products, help with retaining and expanding customer base and shorten time-to-market for new product offerings. 

I can hear you asking, "All this is good, but what MUST I do, to drive an efficient Data Enablement program at my company?"

The Short Answer: Displace your Data/Analytics/MIS managers and leads who have been in a role for over four years. 

The Long Answer: Read on for more on the "Why this is important for you?"

The four types of people in the data value chain

  • Producers: Your customers and front-end operations people who interact with the applications, vendor platforms, social media etc.. And are primarily responsible for generating data for your company.
  • Processors: These are the people and teams responsible for sourcing, storing,  cleansing, transforming, and processing data for consumption. Analysis, Architecture, data engineering, and data platform/infrastructure teams are part of this area. 
  • Preparers: Most companies have MIS/Modeling/Analytics teams that are usually part of the business teams. Sometimes they are within technology functions but primarily are a conduit between processors and planners. 
  • Planners: These are the actual end-users comprising of executives, leaders, and doers who consume the output in the form reports, analytics, and models. They consume the information to plan and make decisions to enable other business functions and activities. They also include the applications, APIs, and BOTs that are running intelligent automation processes and other control and productivity related functions. 

So how do you get the most of your investments in Data?

By focusing on the four people segments above.

Producers: You do not have much control over your external producers, but you can make your web applications and mobile apps to be efficient by enforcing data validation, managed picklists, and autocorrect options that takes care of the quality of data coming into your systems. 

Planners: You can drive focused data literacy and training programs to educate and help with better data utilization. 

Processors and Preparers:  The focus of this article, the one thing you must do to drive data enablement is in the context of this group. Success or failure with data is attributed to several aspects including support, commitment, budget, culture, technology, legacy platforms, complexity, talent and the list goes on.

When the topic of culture comes up, usually most teams and leaders gravitate to data literacy. Changing the culture takes a long time but there is something all leaders must do that helps with changing the culture. 

That brings us to displacing people in the processor and preparer groups. 

Failure rate of data leaders is very high, but do you know that most of the time spent by the leaders charged with driving change within the company goes in fighting internal resistance? Healthy resistance is good for the company, we need those checks and balances to validate if an idea, solution, or approach will stand the test of practical use over a period of time. The resistance I am talking about is the unhealthy one. And besides slowing down and causing wastage, it erodes confidence and drains the positive energy within your teams working to move you to the next level with data and analytics.

Forget pareto principle here, because its not the 20% but the 2% of the people who resist change, is what causes slowness, difficulties, setbacks and failures in data programs. 

Here is the process to take the "first-step" towards Data Enablement:

  • Across the preparers and producers, identify the managers and team leads who have been in their roles for over four years. Sometimes you may find even a few departmental leaders, who joined as analysts or architects and have been in the role for 10-15 years and are now managing the entire group. Those will cause the most difficult hurdles for change. Add them to this list.  
  • Move them to different roles within the company, over a period of time. This can be aligned with the progressive coverage and plan of your data initiatives for the year.  
  • If the people who are moved out still want to help, they can always engage with the data initiatives and help with their SME knowledge. If they want to resist negatively, they will not be effective in slowing down change, as they have lost their power of influence over the functions and teams that they once had earlier. 

Why the four year cut-off?

From my experience in leading data and analytics programs across several global firms, the most resistance came from nay-sayers who have been in the same role for over 5, 10, and even 15 years in some case. They have gotten into the early stages of the company, or programs, or supported the same leader for a long time, that a level of complacency has set in. Such people are reluctant to learn new things, fear the unknown, and desperate to avoid losing the "expert" status. 

They are able to misuse the closeness they have with their teams and their managers and propagate resistive tactics. I have to admit some of the best champions I have had during my tenure also have been in their roles for a long time. But such intrapreneurs will support change and help with it, no matter where they are in their organizations.

Test it out

Now that I have given you the recipe for the first-step to succeed and progress with Data Enablement, will you do it? Do you have the courage to lose and displace the people you have depended on for a long time? Don't take my word for it, try it within your company and function. The biggest hurdle to enabling Data is to clear the clog and without doing this hard work, no amount of budget, technology, talent, or infrastructure thrown at the program will help. 

Before you intend on making widespread use of data across the company and business functions, the first step is to remove the unhealthy resistance. It can only happen if you step in and do what needs to be done. Sponsorship is more than providing the budget. It is about owning up to step up the efforts and fix what needs to be fixed, even if it is within your own function and that means moving your own people. 

Do you want help with your Data Enablement Initiative?

If you liked this article and want me to work with your teams and company leaders in helping drive Data Enablement at your company, let's get started. 



Data Enablement

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