How to Create Data and Analytics Solutions in Complex Landscapes

By Mariyah Saifuddin

Podcast Insights

We keep hearing from clients about the challenges of working with lots of data and a growing number of different systems. That’s why the next series of Tech-Driven Business Podcast episodes dives into how organizations such as yours can successfully tackle data and analytic solutions in complex data landscapes.

Michael Kim, a data and analytics expert with more than 20 years of product management and consulting experience at Accenture, IBM, KPIT, DXC Technology, recently joined Mustansir Saifuddin to share what he’s learned across his career. With experience using myriad tools — including SAP, IBM, Snowflake, Salesforce, and Workday – Kim shared some great steps companies can take to be successful.  

Approaching complex landscapes

A challenge for organizations lies in how to define complex landscapes. “The big elephant in the room for all organization is what is complex?” Kim says.

By serving multiple clients and vendors, Kim understands the challenge. According to him, it comes down to determining if you are working with a process approach or a data-driven approach. This sets the foundation of solving the complexity. 

Then there is more business clarity on process and on the role data and analytics products play in the business.

Defining a complex landscape

  1. A centralized data analytics landscape where multiple regions are consolidated into one centralized data platform which will produce data products to the business, customers and vendors.
  2. A decentralized data environment where multiple regions are handled individually is another way of approaching data and analytics.

There is no right answer. It really starts with the environment of the landscape, what the customer wants to achieve, and where they fit in with the industry. Data products and processes help create a centralized data environment in order to provide clarity and data insights for data products that can serve the customer’s purpose and business users.

Implementation approach

Kim likes to take a step back from applications or business and think about the implementation differently. An organization should assess where it is in its data and analytics journey. 

Are you just starting out and crawling? Or are you walking or running? 

The most important aspect for the organization’s key players is to understand where the organization is in the current state; this allows them to determine how to focus. For instance, start with descriptive analytics and then move on to predictive and prescriptive analytics. Organizations further along in the journey can look at more complex solutions like embedded analytics, artificial learning or machine learning. 

It is a balance of where an organization currently is and where it wants to end up.

Consultant approach

When entering a project, there is value in first understanding where you are as a project, program and company, say both Saifuddin and Kim. 

Once the project and program are clear, think about how to add value by simplifying that implementation approach. Understand your surroundings and your current state, not only for yourself but for the program and the client. Additionally, does the SI role come into picture? Where does the application or software vendor come into picture?

Defining success

Success? Defining it depends on who are we here to serve, Kim says. 

Is it IT, the business or the organization? Both Kim and Saifuddin say they firmly believe in prioritizing “business” first, because it is people who ultimately get you to business goals. 

After that, work on the process. Once people are aligned and a strategy/process is in place, technology comes in and execution can happen. Prioritizing business first also means prioritizing the different layers of the organization. Is it C-level executives, middle management or customers and vendors that will value most from the insights data analytics can provide to make informed decisions? 

Success means that the business today is able to make better decisions for the company than they were in the past. There’s no right or wrong answer.

At the end of the day, the business needs to benefit. If the business is benefiting, then that will allow an organization to grow, which is the whole idea behind analytics, to help the business side of the business and the organization as a whole, to make sure that they are on the right path, they are making progress.

Kim recalls Saifuddin’s comment to him when the two met: “Everything is connected, Michael.”

Both Kim and Saifuddin emphasize that success is enhanced by finding the senior analytic experts that cannot only see it from a technical perspective, but also from a business perspective and from a process perspective but are also able to connect it all for a holistic approach.

Kim ends his comments by quoting Saifuddin’s words when the two worked on a project together: “I’m here for two things: I’m here to add value. I’m here to fix problems. Or I’m here to do both.” That’s a principle that is core for a senior analytics expert, he adds.ultim

Interested in more Tech-Driven Business podcasts? You can listen here

About Michael Kim

Michael KimMichael has 20 years of product management and consulting experience at Accenture, IBM, KPIT and DXC Technology. Michael is responsible for implementing more than 15 data and analytics solutions across multiple industries. He’s a product strategist and expert of the information delivery platforms: SAP, IBM, Snowflake, Salesforce and Workday.

Additional resources

5 Things to Know Before Starting a Data Analytics Project: Mustansir Saifuddin gives his take on things to know to help your team meet timelines, budget and beat the odds to have a successful project. 

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