6 Key Practices for Transforming to a Data-Driven Culture Part 2 of 2
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“Data-Driven” means a few things beyond decision making through facts over intuition. Data driven means facts drive the company to shift processes, automate, empower employees to make decisions, and drive revenue in new way. Data curation is the new digital currency powering the next generation of change in enterprise.
Business data analytics is the technology behind being data driven. It comes in many forms from seemingly simple reports coming out of data warehouses or business intelligence systems, to diagnostic or predictive analytics system that might be used for modelling or forecasting or predicting customer behavior all the way up to machine learning or neural networks like you might find in fraud detection or compliance systems to cogitative designed to continuously learn and improve themselves like traffic operations or “smart” consumer electronics or utility grids. This is a wide area of technology that is so foundational to business that it is a disruptive technology. Think of the competitive advantage a retailer or bank gets if the product recommendation system drives $200M in new business. Even simple use cases like the distribution company that figures out the root cause of product delays or shortages and makes a material improvement to ordering, inventory or staffing that save time and expense. Very quickly, such companies become sustainably better with lower variance in performance, higher efficiency in automation, better decisions made faster, and superior ability to profitably target ever smaller and more nuanced opportunities.
High-Performing Companies Have a 65% ROI for Data Analytics Initiatives
Companies are transforming to being data-driven, with the average project coming in over five times the ROI seen on typical IT initiatives. Top performers have an ROI over three times higher than the two thirds of companies that are “laggards” in this area. High performers also have a 65% ROI for data analytics initiatives. This is over three times the return of the (still healthy) 19% other organizations see… but… spending is both more strategically focused, more likely to be successful.
Candidly, the biggest difference between high performers that get outstanding business results is that they have made business analysis capability maturity a priority. There is no amount of data science or technology that can fix a project that is focused on solving the wrong business problem, or is not using relevant data for the business, or doesn’t fit with the business processes of a company. The leaders in business data analytics – those are the ones that build the right skills into their business analysis practitioners so these professionals can properly support the business.
Most Organizations Aren’t Properly Utilizing Data Analytics
Despite the widespread use of AI, analytics is early in the adoption cycle of 20-30% for most market sectors with most organizations deployments being siloed or still in pilot or discrete stage. Executives know the importance and they are investing over $200 BILLION into the technology annually, but they are generally unhappy with results to date – and frankly, this dissatisfaction is impeding the transformation these companies need to make into becoming data driven organizations..
IIBA recently discussed data and analytics failures and successes with over three dozen business leaders and conducted an independent survey of 300 business leaders to find out what high performers are doing differently. While each business’s experiences are unique, the shared lessons learned highlight the importance of aligning technology and business, as well as having a disciplined and focused approach to data and analytics.
6 Practices Businesses Can Use to Transform to a Data-Driven Culture
IIBA research found six important practices led by business analysis that are essential for organizations that wish to become data-driven. They include:
1) Properly identifying the business problem - Data analytics does not start with data. It starts with uncovering what is valuable to the business and focusing this on answering the right business question. Spending $7.5M to realize the ultimate question of life the universe and everything is 42 is not a data science problem, it’s that the answer has little practical utility. To get meaningful value, the data science team needs to be guided to value, and appreciate but the data of the business and the processes of the business.
2) Ensuring accurate, quality, accessible data - The ability to capture data has become overwhelming. But, in a rich data environment what data element is used? What system is the authority and what system or migration or consolidation or accessibility or compliance issues impact or disrupt getting a specific set of answers with confidence.
A business analysis professional works alongside business, data science and IT teams. In many cases, they are instrumental in structuring the workflows that create the data in the first place. They are uniquely qualified to understand the state of corporate data assets, where to expect challenges, and how to prioritize issues.
3) Understanding, verifying, and reporting results - I want you to see talking stakeholders through results as a wonderful data literacy building opportunity. What data, how managed and in what cadence is it coming into the system and through what lens is the analysis done? Business analysis professionals make the discussion of data relevant to the business and help build the literacy of executives in terms of what’s possible and fuel the dialogue of what has actual value.
4) Influencing decision-makers and driving action - When the line of business is not involved or engaged, analytics projects fail. IIBA found that influencing decision-makers and driving action are tasks usually seen by high-performing companies as belonging to the role of the business analysis professional. These professionals need to be deeply embedded and are usually seen as strategic advisors to the business.
5) Building a data culture and trust in the data - The shift to a data culture takes proof, demonstrable results, and benefits – mothing builds cultural change like success. It also needs to be a team effort. A business analysis professional is a critical part of this journey as they represent the voice of the educator, the users, the interpreter, and the translator between different internal stakeholders.
When involved with analytics solutions from the beginning, and when encouraged to use their competencies of problem-solving, reengineering, and communications, business analysis professionals can become influential data champions.
“Data culture and buy-in take time,” Cameron Davies, Chief Data Officer, Yum! Brands, said. Business analysis professionals often reduce the time it takes businesses to build a data culture.
6) Redesigning workflows to integrate analytics in business processes – The business creates data, just as having better data changes the way an organization does business. Answers that enable the organization to function differently… those are valuable! Top organizations do not limit themselves in their process redesign ambitions – they want to redefine how they operate to be more efficient, more agile, and more productive.
Robert Knecht, Director, Public Works, City of Memphis, explained, “Business analysis plays a crucial role in baselining and redesigning processes and automating workflows.” A business analysis professional looks at process reengineering with a wide lens and is the best individual to grasp the impact analytics will have on processes, including the best way to improve workflows to meet the needs of the business.
IIBA research shows companies that have created a data-driven culture follow these six practices. Others do not. Clearly, business analysis professionals are key to achieving transformation into a data-driven organization. Without business analysis led by business analysis professionals, companies will compound their problems. Used properly, they will amplify solutions.
Learn to Achieve More with the Data You Have
Business analysis enables companies to achieve more with the data they have, and to properly gather data from the start. Detailed findings on driving value through business analysis and the six business data analytics practices required to implement the data-driven organization are described in Achieving More with Data.
Here is a breakdown of what the five-part series covers:
- Current Data Analytics Environment: Learn about analytics drivers focusing on the forces at work and the current state of analytics. Access Part A
- Data Analytics Business Impact: Review real-life concerns about companies rushing into business data analytics, putting solutions before problems, and lacking discipline around stakeholder engagement and goal clarity. Access Part B
- Quantifying Capabilities Leading to Success: 300 surveys quantify the six important practices critical for any organization striving to become data driven. Access Part C Summary and Part C Full Report is available to IIBA Corporate Members.
- The Impact of Business Analysis: Key highlights of the impact of business analysis in driving increased ROI or reduced failure rates in data analytics projects. Access Part D
- Driving Value Through Business Analysis: An executive report that details key skills required to implement the data-driven organization for IIBA Corporate Members. Part E Coming Soon
IIBA’s Global Corporate Program provides the support and resources organizations need to build business analysis capabilities and drive professional development and growth in support of data analytics initiatives.
To learn more, fill out the form below to speak with a Corporate Program Manager.
Related Articles:
- Impact Of Business Analysis in Becoming A Data-Driven Organization, Part 1 of 2
- The Importance of the Business Data Analyst Role on a Project Team
- Building Your Business Data Analytics Team
- Why Research Is Essential in Tackling Challenging Business Problems
About The Author:
Keith Ellis brings to IIBA more than 20 years of leadership experience including roles as CEO, COO, board member, investor, and mentor to various companies. He has experience with IDC, CGI, IAG Consulting, EnFocus Solutions, and Anow, among others, and co-founded and sold Digital Mosaic, a business analysis company. A recognized voice in the business analysis community Keith has published and spoken extensively with the Enterprise Architecture Symposium, Business Analyst Times, Modern Analyst, and other outlets in the field in addition to his contributions to IIBA.
