[et_pb_section fb_built=”1″ admin_label=”section” _builder_version=”4.16″ global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_row admin_label=”row” _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” width=”auto” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||” theme_builder_area=”post_content”][et_pb_text ul_item_indent=”30px” admin_label=”Text” _builder_version=”4.22.2″ header_3_font_size=”19px” header_4_font_size=”15px” background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}” theme_builder_area=”post_content”]If inventory is the lifeblood of your business, then inventory management is the circulatory system.<\/p>\n
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For a small business, it\u2019s the difference between thriving for decades or shutting down within a year. For large companies, it\u2019s the difference between outpacing the competition or burning money that could be used on innovation on your operations.<\/p>\n
As technology upends businesses across industries, it\u2019s disrupting traditional functions within businesses as well. Supply chain management, and its subset, inventory management, are no exception.<\/p>\n
Today, real-time inventory management software helps business owners make decisions about their goods by evaluating a wide range of data including:<\/p>\n
New technology, cloud-based services, and the increasing digitization of the supply chain has made this possible and presents exciting implications for all businesses and their warehouse operations.<\/p>\n
Contents<\/p>\n
Inventory is a major pain point, and people are always coming up with ways to relieve it.<\/p>\n
When pen and paper became a hassle, businesses bought mobile barcode scanners<\/a> that fed into databases and produced detailed spreadsheets.<\/p>\n When Excel workbooks and all those sheets, tables, and complex formulas became too much to manage, businesses purchased software that streamlined the process. Now they use historical data to predict future demand<\/a> in an effort to avoid stockouts and keep customers happy.<\/p>\n What characterizes the current state of inventory management is a reliance on forecasts. As the adage goes, \u201cPast behavior is the best indicator of future behavior,\u201d so businesses used a combination of experience, formulas, software, and a little gut instinct to order stock.<\/p>\n Now, imagine a business landscape where owners possessed a real-time view of their inventory data that evaluated several variables to indicate just how much to order.<\/p>\n This is where inventory is going.<\/p>\n We\u2019re in the midst of an inventory management revolution. Traditionally, supply chain managers relied on past stockouts and sales data to make inventory purchase decisions<\/a>. As shopping and supply chain management becomes more digitized, it\u2019ll be possible to incorporate all sorts of product interactions into purchase decisions such as:<\/p>\n In other words, the ready supply of data will make real-time inventory management possible and effectively revolutionize how businesses manage their stock.<\/p>\n Predictive analytics is a subset of advanced analytics. In most cases, the term is used interchangeably with machine learning. A large quantity of data about a given question is collected<\/a> and an answer is spit out. Take this example:<\/p>\n Naturally, this extends to inventory management. Based on what we know about this product, online interactions, and your historical data, demand will go up by 40 percent over the next quarter.<\/i><\/p>\n But as Harvard Business Review<\/i> warns, introducing data science and predictive analytics to your business isn’t as simple as adding a data scientist<\/a> and stirring. It requires an enterprise-wide effort to put the correct infrastructure in place and integrate data to derive intelligent insights.<\/p>\n Generally speaking, implementing a \u00a0successful predictive analytics project requires the following steps:<\/p>\n People often assume that predictive analytics is a panacea that will solve all business problems and give companies psychic abilities. With machine learning, you\u2019ll be able to predict what customers want, rapidly identify inefficiencies, and beat your competitors.<\/p>\n Unfortunately, it isn\u2019t that easy.<\/p>\n You see, predictive analytics relies on data, and even if you\u2019ve got a lot of data, you\u2019ve got to make sure the data you\u2019re using is relevant. The only way to determine the relevance of your data – and do so in an organized, consistent manner – is by clearly defining what you want to achieve.<\/p>\n So for a retailer, the objective may be to \u201cImprove the accuracy of inventory management<\/a> to avoid stockouts and reduce carrying costs.\u201d This can be achieved by daily inventory tracking<\/a> with the help of an warehouse inventory management software<\/a>.<\/p>\n Your predictive analytics or machine learning is only as good as the data teaching it. For this reason, 80% of the hands-on work required to launch such a project is preparing the \u201ctraining data.\u201d<\/a><\/p>\n So how do you go about collecting the data you need?<\/p>\n Well, as we discussed earlier, a lot of factors determine inventory, and some are more obvious than others. The digitization of all sorts of data makes it possible to incorporate everything from natural disasters to social media chatter about your brand into your inventory control<\/a> and management predictions.<\/p>\n Some of the factors a real-time warehouse\u00a0management system<\/a> built on predictive analytics can take into consideration include incoming orders, digital marketing statistics, and more.<\/p>\n It can even consider the impact of weather and pull out insights that go beyond predicting that demand for shovels increases in winter.<\/p>\n Case in point: several years ago, Walmart discovered that strawberry Pop-Tarts would sell out whenever meteorologists reported a hurricane<\/a>. The reason was simple: They\u2019re a tasty snack with a long shelf life that doesn\u2019t require refrigeration.<\/p>\n Consider all kinds of sources when collecting data for your inventory control improvement project. Your order management system<\/a>, various tools in your enterprise resource planning (ERP) technology, your marketing automation tools, your WMS\u00a0system or your 3PL System<\/a>, and even the Weather Network<\/a>, can come together to help you accurately meet demand spurred by all sorts of seemingly ridiculous variables.<\/p>\n Your employees enter all sorts of data into your system, but if they skip certain fields, don\u2019t use standardized formatting, or enter inaccurate information, they\u2019ll sully the quality of your data analysis efforts and therefore, the accuracy of your insights. And since you\u2019re pulling data from numerous sources, the impact of errors is multiplied.<\/p>\n Once you\u2019ve collected data from your automated systems, cleaning that data is a pain and includes several tasks including:<\/p>\n Your data cleaning efforts can also be proactive, rather than just reactive. Communicate the impact of bad data to your staff and monitor their compliance with data standardization efforts.<\/p>\n In some cases, updating a database is a low-priority task on an employee\u2019s list of duties, so they may not put as much effort into it. Sharing the benefits of clean data helps your employees understand how the data they provide feeds into larger business objectives.<\/p>\n In the case of warehouses, most of this information is submitted through barcode scanners or radio frequency identification scanners (RFID<\/a>). But information from other parts of the business, such as marketing or sales, also impacts a company\u2019s ability to predict safety stock<\/a> and reorder points<\/a>\u00a0through real-time inventory tools.<\/p>\n You can purchase data cleaning tools to speed up the process<\/a>.<\/p>\n Once your data is clean, consider a software that can speak to all of your platforms that deal with inventory. An integrated warehouse inventory management software could be the solution you\u2019re looking for to keep your data clean.<\/p>\n So what do you do once you\u2019ve collected all that information? How do you go from a bunch of numbers to insights that reduce excessive inventory and ensure accurate inventory?<\/p>\n According to one management consulting firm, there are a few recommended steps companies should take when selecting a data management and analytics tool<\/a>:<\/p>\n What is the current state of data analytics within your company<\/a>? This question extends beyond your warehouse to include your entire organization. Hold consultations with key stakeholders who engage with data most often. They\u2019ll possess insights into what data functionality would be most useful and what your organization doesn\u2019t really need.<\/p>\n By talking to stakeholders, you may find that you don\u2019t need additional data analytics tools. Perhaps your current technology possesses the capabilities needed and your employees just need additional training and education.<\/p>\n Take a look at the current data analytics market landscape<\/a> to build a list of the current solutions on the market. Once you\u2019ve compiled this list, break these market solutions into categories. There are different data analytics tools for different objectives. Types of data analytics tools include:<\/p>\n Once you\u2019ve broken up available solutions into categories, you can better assess which tools meet the needs specified by your stakeholders.<\/p>\n Once you\u2019ve assessed your company\u2019s needs and then categorized the solutions on the market based on those needs, compare your inventory against your competition to assess how urgently you need to upgrade your tech and processes.<\/p>\n Evaluate each of your vendors based on different capabilities. Your scoring should place greater weight on capabilities that meet your business needs. If you have a decent amount of business to award to vendors, you can distribute an RFP that lists your requirements and ask companies to present their capabilities.<\/p>\n Use decision-making software to plug in your variables and requirements and come to an unbiased, fact-based decision. Just like with data analytics, the results provided by your decision-making software is only as good as the information you feed it, so be sure to conduct thorough research on different vendors. As an alternative, you can use a manual decision-making matrix.<\/p>\n Whether you\u2019re a large B2B company or a B2C company<\/a>\u00a0selling fast fashion, keeping your customers happy is important. Customers can be fickle and unforgiving.<\/p>\n They\u2019re even more particular in B2C where they have endless options. In fact, 50% of online shoppers will abandon a full cart<\/a> if one item they want is out of stock. Real-time inventory management helps shaping your ecommerce customer experience<\/a> by avoiding stockout, satisfing customers, and turning them into repeat customers.<\/p>\n Inaccurate inventory counts have a domino effect. If you don\u2019t know how much inventory you have, you don\u2019t know how much inventory you need to order, and you can\u2019t properly predict stockouts.<\/p>\n The sheer frequency with which inventory moves, whether it\u2019s due to orders, spoilage, or damage, makes it hard to stay on top of the exact amount of inventory.<\/p>\n On the other hand, a real-time inventory management system accounts for all <\/i>movements by receiving real-time data from your:<\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row _builder_version=”4.22.2″ _module_preset=”default” width=”auto” custom_margin=”15px|auto|15px|auto|false|false” custom_css_main_element=”.hbspt-form .legal-consent-container a {|| color: white !important;||}” locked=”off” global_colors_info=”{}” global_module=”26788″ theme_builder_area=”post_content”][et_pb_column type=”4_4″ _builder_version=”4.22.2″ _module_preset=”default” use_background_color_gradient=”on” background_color_gradient_stops=”#481a96 0%|#200741 100%” custom_padding=”15px|35px|15px|35px|true|true” border_radii=”on|10px|10px|10px|10px” global_colors_info=”{}” theme_builder_area=”post_content”][et_pb_text _builder_version=”4.22.2″ _module_preset=”default” header_3_text_color=”#ffffff” header_3_font_size=”30px” header_3_font_size_tablet=”30px” header_3_font_size_phone=”20px” header_3_font_size_last_edited=”on|phone” global_colors_info=”{}” theme_builder_area=”post_content”]<\/p>\n [\/et_pb_text][et_pb_code _builder_version=”4.22.2″ _module_preset=”default” text_orientation=”center” global_colors_info=”{}” theme_builder_area=”post_content”]The Future State of Inventory Management<\/h2>\n
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Launching Real-Time Inventory Management Takes More Than Hiring a Couple of Data Scientists<\/h2>\n
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Clearly Defining Your Business Objective<\/h3>\n
Collecting Ample Data From Relevant Sources<\/h3>\n
Improving Your Data\u2019s Quality Through a Data Cleaning Project<\/h3>\n
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Select a Predictive Analytics Tool<\/h3>\n
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Conduct a Research and Discovery Initiative<\/h4>\n
Understand The Data Analytics Market Landscape<\/h4>\n
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Compare Your Company Against Others With a Capability Tree<\/h4>\n
Create a Decision Matrix to Compare Different Vendors<\/h4>\n
Use a Decision Tool to Make The Final Call<\/h4>\n
Why Does Real-Time Inventory Management Matter?<\/h2>\n
You Keep Your Customers Happy<\/h3>\n
Pull from Accurate Inventory Counts<\/h3>\n
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Request a free demo to learn more about Logiwa WMS.<\/h3>\n