Why an Entire Digital Transformation Is Essential for Supply Chain Success
Sea changes in market direction and product requirements that previously developed over long periods of time can, today, occur overnight, driven by a range of economic, business and buyer demands that force manufacturers to switch gears immediately in order to meet personalized customer needs.
While most supply chain executives say they understand the importance of precise data management to assure sufficient stocks are available in order to avoid costly production downtime, a large number also admit they still rely on a patchwork system of spreadsheets and manual inputs, methods fraught with the potential for human error. Such manual tasks may have been “just fine” in the past, but in today’s rapidly changing marketplace, anything less than 99-percent accuracy in data gathering, input and analysis throughout the organization can spell disaster.
Ongoing success now demands a digital transformation of operations from top to bottom that enables an agile strategy with instant adaptability to shifts in market trends and changes in customer requirements, as well as the ability to collect, consolidate, assemble and analyze real-time, up-to-the minute data.
It’s a comprehensive mission that, while proven to bring bottom-line success, still confounds many executives and department heads all along the supply chain.
Defining Digitization Up and Down the Chain
Digitization means different things to different parts of the supply chain operation. At its simplest level, it is a technical exercise aimed at converting analog information into a digital format followed by digitalizing internal processes.
From an executive-level strategic standpoint, it represents a transformation of a company’s business approach, one that impacts each unit from the C-suite to the plant floor in different ways, but integrates all of the latest data so it triggers an entire digital remodeling of operations. It’s a corporate commitment to provide every department in every division at every location with immediate access to harmonized and continually updated, real-time data sets.
To do so, company leadership also must balance the stakeholder appetite for cost efficiency and short-term profitability with the greater blueprint for long-term revenue growth offered by a full-scale transformation of the corporate business model.
At the mid-management level, digitization means going well beyond the need for a trusted data foundation and moving deeper into the real-time insights needed to deliver true supply chain intelligence. It is visibility these supply chain professionals crave―not only across ERPs and other disparate systems but also throughout the entire supply chain ecosystem (partners, suppliers, customers, etc.). With the newfound, more reliable visibility that digitization affords, managers and directors can confidently build more efficiency into their supply chains, reduce manual processes and more easily find ways to decrease working capital expenditures through improved procurement and predictive inventory.
On the plant floor, the digitized harmonization of data allows personnel to quickly alter inventory requirements, adjust the stocking of products as markets and customers shift direction and establish a uniform naming convention process so that everyone is inputting data into a single format that eliminates confusion up and down the line. It also helps avoid unnecessary production stoppages as plant personnel search for misplaced inventory and prevents the wasteful ordering of duplicate products that already may be in stock but labeled incorrectly and located elsewhere in the plant.
For the supply chain, it comes down to an approach that successfully embraces flexibility and adaptability to benefit from today’s rapidly changing customer and manufacturing environment.
The New Path to Digital Success
In the past, companies expected departments to fix specific, immediate problems within individual data silos, an approach that no longer works because of how interconnected everything is, according to Jeanne W. Ross, principal research scientist at the MIT Sloan Center for Information Systems Research, during a Harvard Business Review webinar on agile IT and digital transformation.
“Now we have to basically duplicate what digital startups do,” Ross said. “We have to try an idea and see if it works, and it won’t, so then we have to try another idea and see if that works, and then just kind of zero in on what our customers would like and what we can do, and then make that work, scale it up. It’s a very different world and that demands agility—the ability to adapt and respond to market opportunities.”
The path to digital success means the abandonment of silos and the development of what Ross calls an operational backbone, which includes standard processes and shared data, applications and technology.
Where to Start
“Digital transformation has been mixed in terms of the speed of deployment across manufacturers,” said Doug Gates, global chair of KPMG’s Industrial Manufacturing Sector, in the firm’s Global Manufacturing Outlook 2018. “Some have organized well and jumped on it. Some have gone on a technology splurge, but ROI has been elusive. And many are still struggling to decide what to do and where to start.”
In the KPMG Outlook, based on data from 300 manufacturing industry CEOs, two-thirds said they are prepared to lead a transformation of their company’s operating model, but 70 percent expressed “overwhelming” concern for lead times required for implementation. And, more than half cited “an unreasonable” expectation by their boards of directors for ROI.
“The right first step is to lay out a long-term strategy and roadmap,” said KPMG’s Gates. “Start the journey with steps that will achieve near-term value, while laying the foundation for new business opportunities that will come from interconnectivity and a broad access to data and information.”
A well-developed, comprehensive digital transformation, boosted by artificial intelligence (AI) and machine learning solutions, replaces the outdated approach that treats internal business units as standalone enterprises with separate data collection, assembly and reporting—a time-consuming approach to market analysis that misses critical trends taking place in today’s fast-moving markets.
By comparison, AI and machine learning speed up the entire process by “harmonizing” all of that data contained in the separate system silos, factoring in and instantly evaluating individual customer purchasing practices, up-to-the-minute market conditions, regional trends and other data to provide valuable predictive analysis of upcoming supply needs approaching more than 90-percent accuracy. This is what AI brings—speed, accuracy and scale.
Such technology allows manufacturers and distributors to continually monitor the latest data to enable meticulous inventory management decisions without being bogged down under outdated, manually-driven analytical procedures.
By leveraging the latest available advancements, such as digitization and AI-based predictive analytics, manufacturers and distributors can infuse their data foundation with the knowledge and understanding needed to create an intelligent, connected supply chain—one driven by new technology, clean and harmonized data, business adaptability, total inventory accuracy, a keen focus on the customer experience and a long-term but flexible strategy for growth and success into the future.