What is Digital Transformation?
A digital transformation requires that companies transform their decision-making processes with technology to enhance customer experience and employee productivity and ultimately improve business performance. Technologies such as artificial intelligence, machine learning, Internet of Things, and virtual reality can aid in this transformation.
Digital transformation implies shifting the way organizations interact with their customers and the way they make business decisions. In the Supply Chain Planning context, these include decisions about which products to keep in stock, where to keep them, when to replenish them, how to improve service levels for customers, how to liquidate excess stock in the most profitable way, how to respond to changes in customer demand in the most agile way, etc. These shifts include real-time tracking and analysis of customer and product data, decision-making based on predictive and prescriptive models, using new technologies such as machine learning, and automation of daily operational decisions. As many organizations have experienced already, legacy systems cannot keep up with their needs.
As Jeff Bezos, the CEO of Amazon, has said: “Day 2 companies make high-quality decisions, but they make high-quality decisions slowly. To keep the energy and dynamism of Day 1, you have to somehow make high-quality, high-velocity decisions. Easy for start-ups and very challenging for large organizations…. Plus, either way, you need to be good at quickly recognizing and correcting bad decisions. If you’re good at course-correcting, being wrong may be less costly than you think, whereas being slow is going to be expensive for sure.”
3 Steps Organizations Need to Take to Make Digital Transformation Happen
1. Pushing for Speed, Mobility and Data Democratization
Speed in decision-making and execution is critical, particularly for companies that understand the importance of getting closer to their customers. This is emerging as the top differentiator for businesses as they re-organize to support agile decision making and digital transformations. However, we often see business intelligence as a separate solution built on top of a data warehouse and used mostly for reporting, and dashboards, data visualization and extracting data for further offline analysis. These all slow down an organization’s ability and agility to respond to customer needs. In the digitally-transformed world, weekly decisions are turning into daily or hourly decisions. Reports generated by data downloads from separate databases and pasted manually to spreadsheets do not suffice anymore.
Ted Colbert, the CIO of Boeing, hammered this point home. “You have to figure out how to really democratize the data-analytics capability, which means you have to have a platform through which people can easily access data. That helps people to believe in it and to deliver solutions that don’t require an expensive data scientist. When people begin to believe in the data, it’s a game changer: They begin to change their behaviors, based on a new understanding of all the richness trapped beneath the surface of our systems and processes..”
Data analytics cannot stay within the realm of the few data scientists anymore, information needs to be accessible real-time, presented in an actionable way, and accessible by all levels in the organization.
Ibrahim Gokcen, chief digital officer, A.P. Moller – Maersk has made the same point, “Data has to flow across the organization seamlessly. Now that our data is democratized, thousands of people can access it for their daily work. We see a lot of energy.”
2. Bringing Agility into Supply Chain Management
As companies explore their own paths to agility and digital transformation, existing legacy systems often come up as the main limitation. Agility calls for encouraging teams to come together and take accountability for end to end processes related to products or services offered by the business. However, we often see that legacy systems for analysis and decision making are separate and disconnected from operational execution systems. This goes for Supply Chain Management and the surrounding IT infrastructure as well. Even today, in most of the businesses, Supply Chain Planning and Management systems have been configured to serve very specific roles and/or functions organizations. In many cases, different planning and execution decisions are being managed in different tools and require manual interventions and data feeds. Collaboration with outside vendors is still very manual and disconnected. Information flow, for the most part, is managed across multiple platforms by sending documents and spreadsheets back and forth. Digital transformation requires integrated planning capabilities with concurrent analytical models combining forecasting, inventory planning, purchase order management and logistics decisions as well as real-time online collaboration with vendors, minimizing need for manual data input, automating data flow as much as possible.
3. Migrating to Cloud-Based SaaS Solutions in a Test-and-Learn Manner
The business environment is changing fast, new data sources are being utilized, and new technologies are being introduced continuously. Organizations need flexible, scalable, and configurable solutions that can be updated seamlessly and accessed anytime and anywhere. This is where cloud-based SaaS solutions are a big help. However, there is still the question of where to start and how to transform all of the processes to a new digital way of working. Of course, all of that doesn’t happen overnight. The bigger the organization, the older the legacy systems, the harder it is to leave behind the old ways of working and adopt new technology and processes. Changing over to cloud-based solutions should not replicate the existing silos, but rather focus on an end-to-end process and start small and build from a Test & Learn approach. Since culture plays a big role in the success of digital transformation efforts, it is best to initiate the change in a segment of the business. Doing so increases the chance of success, provides the organization with proven benefits, and creates a success story to support additional initiatives. Looking for opportunities to automate decisions in the end-to-end planning and execution cycle of one product category would be an example of such a measured approach. In the case of CPG companies, this could mean looking for ways to link the interrelated decisions along the supply chain. For instance, sudden changes such as peaks or drops in demand automatically can update future forecasts and trigger changes in supply plans and update production plans or purchase orders . An integrated workflow would link and automate data analysis and decision-making for:
- Managing supply and demand
- Sourcing raw materials and parts
- Manufacturing and assembly
- Warehousing and inventory management
- Order entry and vendor management
- Inbound transportation management
- Outbound Distribution across all channels
A recent Forbes article features a success story by a global CPG company. This company, with their partner Solvoyo, initiated a Test & Learn process. In this case, Test and Learn has proven to be more effective than doing a pilot. This Test and Learn process lowered costs, led to a faster delivery of the solution, which resulted in a more immediate improvement in the business’s end-to-end planning process. The solution is now proven and can be scaled to other categories and geographies.
In the case of retailers, digital transformation of the daily/weekly decisions such as Markdown Management (in fashion), Purchase Order Management and Store Replenishment are the most common starting points. With automated decision-making, a multi-national fashion retailer can manage markdowns in 30 countries with local pricing decisions. All this can be done with a small central-planning team with limited resources. Retailers can open new stores, and replenishing them, without growing their allocation teams. Similarly, a fast growing e-commerce company can automate inventory and purchase orders with predictive analytics while reducing inventory costs per SKU. All of these transformations can happen within months without having to spend millions. So why wait?
Asena Yosun Denizeri is the Senior Director of Retail Solutions at Solvoyo. Ms. Denizeri has more than 20 years of experience in implementing Planning, Pricing and Optimization solutions in global companies in U.S. and Europe. She has led cross-functional teams in large-scale projects touching different points in Retail lifecycle, including Category Planning, Assortment Localization, Demand Planning, Size Optimization, Promotion Planning, Allocation and Replenishment, Markdown Optimization and Supply Chain Management. Following her consulting tenure with Silicon-valley based software companies, she brought her Advanced Analytics and Business Process Engineering experience to Apparel Retail where she worked at Gap Inc. and Cache where she led Merchandise Planning and Distribution teams to adopt new capabilities in Forecasting, Assortment Localization and Price Optimization to improve sales and profitability. Ms. Denizeri holds a B.S. and Master of Engineering degree in Operations Research and Industrial Engineering from Cornell University. She is one of the contributing authors in Oxford Handbook of Price Management and has been a guest lecturer in San Francisco State and Columbia University business school on multiple occasions.