The new generation of high-performing dairy companies has one commonality: the ability to leverage and analyze data to make better supply chain decisions. Today's milk supply chains are highly data-dependent. Data delivers insights that can help dairy leaders track and manage milk supply chains with the ability to make informed decisions.
Yet, many dairy leaders feel they are still making educated guesses despite drowning in a data deluge. The frustrating lack of complete, consistent, coherent, and compatible data makes analytical success near impossible or immensely time-consuming. Deloitte's recent survey found that only 16% of respondents felt their enterprise had effective data systems to enable vital strategic initiatives better. How can your dairy company ensure all data collected is usable and aligned with supply chain goals and values?
The problem
There is a need to collect data for milk quality and compliance in the milk supply chain– this has expanded to sustainability, optimization, and traceability in recent times. Typically, industry data is captured without clear guidelines or objects. This has resulted in the all too familiar situation of implementing multiple systems across the milk supply chain to capture data for dairy companies. The problem with this structure is that each design is disparate from the next. Thus, data does not automatically and seamlessly flow throughout the milk supply chain.
This typically structured approach to capturing data transfers information between systems manually via text files, resulting in human errors, unclear communication, out-of-date data, and significant inefficiencies. The consequence of this reporting becomes inaccurate. It is the old analogy - if rubbish goes in, rubbish will come out.
Most milk supply chain leaders agree that available data is difficult to correlate because it is siloed in several ways, due to disparate tools and standards, or simply because it is insufficient data. Fragmented and inconsistent data delays time-to-market, increases milk forecast errors, produces wrong milk production planning, and creates inefficiencies. In this all too familiar scenario, data collection has become a burden rather than a benefit to the company. A data collection monster is beginning to form.
So how can you extract consistent, accurate, and clean data promptly that will benefit your business? The answer is an all-in-one seamlessly integrated, configurable, centralized repository solution.
A centralized repository system defines, stores, and manages all mission-critical data. It provides a single-source, trusted view of data across the milk supply chain. Dairy leaders from companies of any size, language, or location can use a centralized repository to remove redundant data and succeed in leveraging data for their competitive advantage. Here are four compelling reasons why a centralized repository (CR) can help dairy leaders successfully leverage their milk supply chain data:
A single source of truth in a data deluge
How can a CR ensure you have the correct data analytics to make truly informed decisions? It helps consolidate, cross-reference, cleanse, validate, and store data automatically, providing a transparent and all-inclusive end-to-end view of the milk supply chain.
With a CR, information like milk quality tests, producer supply, tanker tracking, and forecasting are standardized and accessible to everyone across the milk supply chain. Hence, it allows data to move in real-time, accurately, and with optimization.
How does this work? Let's focus on the example of milk quality. When a dairy company utilizes a CR - milk samples generated by the LIMS system - will be matched with the farm, date, pickup, vat, and manifest/run. Ultimately this means, if quality issues in the milk show up, the dairy company can trace back to the producer or hauler to remedy the problem in real-time, without loss or waste of manufactured product.
Standardization and transparency across the organization
Currently, siloed departments are an issue, resulting in failing data visibility. A significant disadvantage – many company decisions rely on visibility. Standardization of business systems and merging data is the first step to achieving supply chain transparency.
A configurable and flexible CR contains all vital information for the milk supply chain (e.g., scheduling, payments, milk quality, producer compliance, company compliance, sustainability, and auditability). Consistent and cumulative collection and storage of this data ensure the utmost transparency.
CR is beneficial for onboarding new partners, producers, and haulers because everything is contained in one platform. Thus, it is more convenient to identify cost optimization opportunities.
Assistance in operations & forecasting
CR facilitates the smooth transaction of information across the milk supply chain network. Standardization of data ensures compliance with regulations, social norms, and legalities. Thus, internal and external parties can collaborate, providing accurate financial data, faster automatic payments, and reduced administrative labor.
For example, when producers use the same CR system – the dairy company can access the producer's budgeted and forecasted production. Thus, they can leverage and compare this information against their budget. So, ultimately using their single source of truth, they can compare actual production versus their own budget/forecast in real-time. Any changes in real production can then be adjusted and responded to by the dairy company. Consequently, cost efficiencies are gained through enhanced accurate forecasting and budgeting.
Smart management and sustainability
In an era where all companies are interconnected, having a fragmented approach to milk supply chain data - using multiple systems and units - is outdated and unsustainable.
The good news is that even if your dairy company faces such a situation, it is not too late or too difficult to change. Consider the following example:
Nestle was an extreme case of collecting data and finding it very difficult and costly to analyze. They had 27 different data systems across their milk supply chain. Each with various vendors, rules, databases, structures, and locations. A prime example of drowning in a data burden.
The result? An inability for centralized reporting and analysis. By relying on each of the databases to provide the information, up to 12-month delays could occur. Leveraging data was obsolete with this structure.
Recognizing the need for improved control over their milk supply chain, Nestle switched to an all-in-one seamlessly integrated, configurable solution to quickly and easily make changes as required for their database globally. The result? Nestle now can collect any data needed and have the ability to have their entire milk supply chain data interacting in real-time. Thus, they can leverage and analyze their data in a way that was 'unthinkable' beforehand. "We are saving around 80% in our maintenance costs by using MADCAP." - Tomas Vera, Nestle Digital Innovation in Operations & Agriculture Lead.
Like Nestle, do your research, check references, and choose a proven solution. Make sure you select a world-leading expert who can adapt to the dairy industry's ongoing changing requirements, and you will benefit from improved efficiency, measurable savings, and better traceability.