Six business intelligence challenges IT teams must address

Business intelligence (BI) enables businesses to gain insights from large amounts of data. But doing so requires overcoming a number of strategic and tactical challenges.

Currently, organizations of all types are inundated with data from a variety of sources, and trying to make sense of it all is overwhelming. Therefore, a strong business intelligence (BI) strategy can help organize processes and ensure business users are able to access and act on business insights. Through BI strategies, various data sources can be integrated to provide users with accurate and useful information. The benefits of a BI strategy are many. First, it helps organizations better understand their business data and provide deep insights. Second, a BI strategy can also help organizations manage and analyze large amounts of data, from

Lisa Thee, head of good industry data at Seattle-based Launch Consulting Group, said: “By 2025, it is estimated that we will generate 4.63 terabytes of data every day. Data. For businesses to stay connected to the market, react to it, and create products that connect with consumers, it’s important to leverage the insights generated by this information.” This growth in data volume means businesses need to collect, store and analyze data more efficiently to gain meaningful insights. At the same time, it also provides the opportunity to connect with consumers and create products that are aligned with their needs and preferences. The insights generated by leveraging this information can help businesses make more informed decisions and maintain a competitive advantage in a competitive market. To address this massive data challenge, businesses need to invest in advanced business intelligence software that helps companies do this by channeling the right data into analytical reports and visualizations so that users can make informed decisions. decision. But without the right approach to implement these tools, organizations are still faced with maximizing value and achieving business goals.

Here are six common business intelligence challenges enterprises face and how IT departments can address them.

1. Low user adoption

Business intelligence tools play an important role in enterprises. Gaining buy-in from all stakeholders is critical, as any initial reluctance will lead to low adoption. In driving the adoption of business intelligence tools, the following points are critical: 1. Clear goals: Make sure the goals and expected results of the business intelligence tool are clearly defined and communicated. This will help stakeholders understand the tools’

“For our business intelligence team, The first issue is convincing people that business intelligence will help make truly data-driven decisions." Schellman Corporation is a consulting firm specializing in information security, privacy and compliance. Their team of business analysts is dedicated to delivering the business intelligence solutions their clients require. Business intelligence is the ability to transform data into meaningful insights and actions that can optimize business operations, increase efficiency, and increase profits. In today’s digital age, data is everywhere

To gain employee buy-in, Stout’s team built business intelligence dashboards to show them how to easily connect and interact with data, and in an effective way. Visualize data in a meaningful way. The dashboard not only provides real-time updates of key data, but also presents it in an intuitive way that allows team members to better understand and leverage the data. In this way, team members can better understand the business situation, make decisions quickly, and improve work efficiency

She said: "For example, a certain stakeholder believes that a certain product line is profitable. I You can build a dashboard that shows them intelligence that either proves their idea is right or proves them wrong and shows them why." Stout said this allows users to see adoption The value of business intelligence tools.

2. Determine which business intelligence delivery method is best

There are many traditional IT management methods for delivering reports and insights from data. But by using self-service business intelligence tools, along with more intuitive dashboards and user interfaces, companies can derive greater business value from their data by streamlining processes by giving managers and other non-technical staff better access to reports.

However, there can be obstacles to adopting a self-service approach, said Axel Goris, global head of visual analytics at Novartis, a multinational pharmaceutical manufacturer based in Basel, Switzerland. For example, having too much access across multiple departments increases costs and exposes the business to data security issues. Want your sales team to make decisions based on whatever data they get, and have the autonomy to mix and match to see what works best? Having centralized, standardized control over tool rollout is key. To do this properly, IT needs to manage data well.

Because of these trade-offs, enterprises must ensure they choose the business intelligence approach that is best suited for the business application at hand.

Axel Goris said: "In addition to the external employees who work for us, we have more than 100,000 employees, which is a quite large user group. A key challenge is around the delivery organization, how do you organize delivery, because pharmaceutical companies Highly regulated."

Goris explained that the IT-managed business intelligence delivery model requires a lot of work and processes that are not suitable for some parts of the business.

Goris said, “This is because they feel the game is too complex, there is too much overhead, they want to move faster and be more agile, and if IT is the first place to deliver, then it becomes a bottleneck. , because we are not large enough to provide delivery services to everyone.”

To address this challenge, Novartis has implemented two delivery methods: an IT-managed approach and a self-service, business-managed approach.

He said: “With Business Management Delivery, we provide the platform and tools and allow the business to grow themselves within certain parameters, using their preferred suppliers, or let the team do it themselves, which is very welcome ." He added that it all comes down to deciding "how do we serve everyone in the business, or allow business intelligence users to serve themselves in a scalable way."

3. Whether to integrate data

As businesses find themselves having to integrate data from a variety of data sources on-premises and in the cloud (which can be a time-consuming and complex process), the need to simplify the setup process increases. But many people have found other solutions. For example, Rick Gemereth, chief information officer of Lionel, a North Carolina-based U.S. designer and importer of toy trains and model railroads, said the company uses ERP as its system of record.

He said: "Our single source of data is NetSuite, and our entire ERP and e-commerce is based on NetSuite. One of the benefits of this is that we do not need to face the challenge of trying to combine data from different sources. challenges.” However, what works for Lionel may not work elsewhere. The challenge is to find the solution that works best for your specific situation.

For example, Stout explained how to solve the integration problem of customer relationship management (CRM) and financial data.

She said: "A lot of business intelligence software pulls from a data warehouse, loads all the data tables in the data warehouse, and these data tables are the back end of different software. Or you have a business intelligence tool, For example, Schellman uses Domo, which acts as a data warehouse. You can connect to this software and it will pull it into a table. Then you put all those tables in one place so you can take the information and process it."

##Jim Hare, distinguished vice president and analyst at Gartner, said some people think they need to dump all the data siled from various business unit systems into a data lake.

He said, "But what they really need to do is fundamentally rethink how to manage and access data. Gartner wrote about the concept of data structures."

Data structures are defined as An enabler of frictionless access to data sharing in distributed data environments, designed to help enterprises access, integrate and manage data no matter where it is stored, using semantic knowledge graphs, active metadata management and embedded machine learning. "Data fabrics allow data to reside in different types of repositories, either in the cloud or on-premises," Hare said. "The key is being able to find relevant data and connect it through a knowledge graph. Key to that is metadata management."

4. Data doesn’t have to be perfect

Conventional wisdom holds that businesses need to use high-quality data to gather the necessary insights to make the best business decisions. But Nicole Miara, director of digital transformation at Switzerland-based LKQ Europe Ltd., a parts distributor for the automotive market, said that this statement is not quite accurate.

Just because data isn't considered to be of the highest quality doesn't mean it doesn't have value.

When it comes to decision-making, businesses’ desire for perfect data can slow down their efforts as they spend time gathering as much data as possible, fixing incomplete data or correcting formats. Miara said it's hard to have perfect data, but companies can use and analyze imperfect data and start turning it into business insights.

"The data doesn't have to be perfect to start this journey. It's a step-by-step approach," she said. Furthermore, she added, predictions cannot be made without a basic layer of data.

For example, LKQ Europe is trying to apply its data, including sales data, to improve its supply chain operations as it experiences a 35-month disruption due to the COVID-19 pandemic. However, the company only has about 12 months of historical sales data.

Miara said: "We collected invoice data, but we had no additional information on sales, so used imperfect sales data and tried to find correlations with our future business. But we wanted to know if Our forecasts can be improved to predict demand based solely on this data. We find that imperfect data correlate very well, albeit imperfectly, with external signals such as inflation and employment indexes."

5. Dealing with resistance to change

Change management is the No. 1 challenge when implementing business intelligence, said Nick Schwartz, chief information officer at HappyFeet International, a Georgia-based company that manufactures luxury vinyl and tile flooring.

Schwartz said that in the flooring industry, many people are not using new technologies. In fact, when Schwartz joined the company three years ago, salespeople didn't even use email in their daily work because they were more accustomed to conducting business over the phone.

He said, "People are used to doing things a certain way," and they've been doing it that way for years and they'll ask you why you're trying a different way. Therefore, we must make their experience as simple as possible while extending training time. ”

6. Data governance consistency

Justin Gillespie, chief data scientist at research consultancy and consultancy The Hackett Group, said that enterprises need to ensure that they have mature data governance processes, including data management and Governance around key metrics and key performance indicators (KPIs).

He said, “Every company I’ve been in contact with has the same problem, people are not communicating well with each other, so there is a set of Centrally managed KPIs and metrics for organizational certification are key. ”

Gillespie believes that governance also includes standardized tools and platforms. “From a tools and technology perspective, it’s rarely because of a lack of tools, but because there are too many tools,” he said. So companies should standardize on a toolset and then build a proficiency around it.