3 Analytics Hurdles Distributors Face Heading into 2024
Distributors rely heavily on analytics to generate actionable insights and improve decision-making. The right analytics can drive profitable growth, enhance operational efficiency, optimize inventory levels, and strengthen margins through better pricing.
Analytics helped savvy distributors navigate the supply chain swings of the pandemic, and they can help forward-thinking distributors punch through economic uncertainty as we approach 2024. However, three common analytics hurdles stand in the way:
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The exciting yet intimidating path forward with AI.
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The escalating time and cost to build in-house analytics teams and tools.
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The growing complexity of single-purpose analytics tools, which leads to siloed decision-making, wasted time, and endless debate.
Proactively addressing these hurdles can help you harness analytics to their full potential, equipping your business with the insights to protect margins, grow profits, and drive continued success despite swings in the economy.
All-in on AI: Finding the Right Way to Harness the Power of AI
Artificial intelligence (AI) is a game-changing technology, transforming industries far and wide. Businesses in most sectors utilize it in some form, and projections show the global AI market reaching almost $2 trillion by the end of the decade.
Forward-thinking distributors have been formulating plans to integrate AI into day-to-day workflows by turning raw data into actionable insights. AI can help distributors realize immense upside gains in productivity and profitability while shortening the time to react to trends and market shifts. It can empower sales teams to communicate value while creating a personalized sales experience and help leaders make data-driven decisions that impact the entire organization.
AI is more accessible than ever before. Many tools are free or have a low acquisition cost, making them a compelling investment for leadership teams looking to maximize outputs and insights while limiting fixed-cost additions like headcount and equipment. The limitless potential of AI-driven analytics presents an overwhelming number of options for integration. But how do you thoughtfully integrate AI-driven analytics into your business to achieve the biggest bang for the buck? That’s a question that many wholesale distributors struggle to answer.
You might ask yourself whether purchasing new standalone tools or finding AI modules you can tie into existing software is more effective. You may wonder how various teams should apply AI-driven insights in their workflows. Will it be easy for your sales team to get the right insights at the appropriate time in the sales process? Do they have the confidence and “storytelling” context to apply AI-driven suggestions? How should insights be shared across platforms and between functional teams to maximize AI’s sales potential while reducing inter-departmental friction?
What about inventory processes and performance? Pricing and margin analysis? How will you use AI-driven analytics to improve those facets of your business?
Overcoming AI Integration Hesitations
Going all-in on AI technology holds so much promise. However, the first step to success is addressing potential disruptions. That means facing hesitations head-on to embrace AI with confidence.
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Step 1: Assess Your Readiness for AI
First, uncover what potential pain points might emerge with adopting AI. It's about getting a deeper understanding of possible organizational and departmental hesitations based on what you're already doing (and not doing) with analytics. Is your team currently embracing analytics, or are they resisting them – perhaps even viewing them as a threat? Figure out how AI might disrupt your sales team or what it might do to change customer- and supplier-relationship dynamics.
That knowledge will help you implement AI strategically while avoiding common pitfalls.
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Step 2: Understand How AI Can Benefit Siloed Departments
Next, you must appreciate what AI-driven insights can do for your business. Look at your various departments and understand how AI can benefit them at a detailed level. The beauty of this technology is that you can implement as much or as little as you need.
Find where AI-driven distribution analytics can improve efficiency to narrow your implementation approach and pave the way for better results.
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Step 3: Integrate AI Into Existing Software and Dashboards
You don't have to adopt brand-new platforms. The bigger the project, the more likely distributors will procrastinate taking the plunge. Starting small with simple, modular analytics AI capabilities that build on top of existing software systems your team already uses can facilitate a faster, smoother transition.
It's important to demystify AI further by integrating it alongside your core dashboards to support AI-driven recommendations. AI is often "black box" and lacks transparency, so the more you can supplement AI with what we call "storytelling" context, the more confident your team will be in using AI in everyday use cases.
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Step 4: Deliver the Technology with Training and Education
Finally, provide ample hands-on training and education. One hurdle many companies face when introducing AI technology is a lack of adoption due to the perceived skill curve. Combat that head-on by helping them see first-hand how simple it is to use the technology to enhance performance and overall productivity.
Training and education should focus on building on top of existing processes. For those familiar with "habit stacking," pioneered by James Clear in the book "Atomic Habits," you can make AI usage routine by tying it into everyday activities and processes already well-established as corporate habits.
Building New Capabilities In-House is Expensive: Choose to Minimize Costs and Maximize Results
Another hurdle that's affecting distributor analytics is the intimidating potential cost. There are many expenses to consider. One of the biggest? People.
Creating a dedicated, in-house analytics team can be cost-prohibitive for many distributors. According to the U.S. Bureau of Labor Statistics, the median pay for a data scientist is over $103,000 for 2022. That's for a single data scientist with only a bachelor's degree.
Distributors are not analytics software developers by trade, so they often overlook the resources required to build a successful, dedicated in-house analytics team. Forming a team can mean hiring data scientists, database managers, programmers, data analysts, data visualization experts, and tech-savvy leaders who can understand and rally support for analytics adoption. It's a team of expensive resources with advanced degrees.
Building in-house capabilities also comes with a substantial investment of time. Even after you assemble a great team, you need time to reach your full potential and develop quality analytics output. You might also consider the significant opportunity cost of spending time on launches that fail from lack of usage or lengthy implementation.
Finally, you'll need to navigate the complexity of rolling out the tools your team builds and integrating them with multiple data sources. Pair that with adoption hesitation and the constant need to maintain high levels of analytics efficiency to drive your organization's ability to create, share, and apply insights, and it's no wonder that distributors find in-house analytics intimidating. For many distributors, it can be paralyzing.
So what's the solution?
Bridge Analytics Gaps with Outside Resources, Tools, and Training
Establishing complete in-house teams is only a viable choice for select distributors. For everyone else, it can be cost-prohibitive and risky. Fortunately, wholesale distributors can invest in outsourced resources, tools, and training that improve their analytics capabilities at a considerably lower cost.
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Step One: Explore Outsourced Talent
Initial gaps don't need to be filled by full-time professionals. In this new economy, many highly talented professionals can help fill analytical gaps on a part-time or short-term basis until your analytics foundation is ready to scale. It is better to experiment with a series of part-time, outsourced resources than to fail with full-time professionals. You'll also learn a ton by working with specialists on discrete, high-value, short-term projects.
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Step Two: Consider Plug-and-Play Tools
Pre-canned analytics in existing software systems don't always provide sufficiently granular, in-depth analytical insights, so distributors often develop in-house analytics capabilities to fill the gap. As a cost-effective alternative, however, we suggest you consider filling capability gaps with analytics add-ons and plug-ins that work alongside existing platforms.
The right plug-and-play software add-ins offer the power, granularity, flexibility, and customization of an in-house-based analytics solution at a fraction of the cost, a fraction of the time, and with a considerably lower risk of failure. The result: immediate, impactful, and sustainable top-line and bottom-line performance gains.
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Step Three: Invest in Training and Education to Inspire Confidence in Leveraging Analytics in Everyday Decision-Making
Distributors often overspend on analytics development while underspending on the training and education that drive analytics adoption. The worst thing a distributor can do is throw money at additional analytics resources and tools if the analytics ultimately gather dust.
In the absence of education, distribution analytics can be intimidating. You can't always find a single "right" answer in a robust analytical report. Therefore, the most user-friendly analytical reports will help users understand and navigate a series of tradeoffs to explore with customers, suppliers, and other internal stakeholders to arrive at profitable, win-win outcomes.
Education and coaching around core distribution principles (e.g., pricing optimization, inventory optimization, supply chain optimization) are essential when rolling out analytics tools to inspire the confidence to make data-driven decisions and navigate challenging conversations.
Distributors no longer need to break the bank when building out analytics capabilities. It's possible to develop an appropriate mix of internal and external resources to ramp up analytics expertise cost-effectively. You just need to arm users with the right plug-in tools and the right training on core best practices along the way.
Single-Purpose vs. Multi-Function: Overcoming Siloed Decision-Making and Associated Frustrations
Finally, let's address a common but often overlooked issue that can stand in the way of analytics adoption. Single-purpose analytics tools naturally evolve and become more complex and "siloed" as independent departmental needs mature. For example, sales analytics will transition from simple customer reporting to more complex analytics that include forward-looking customer insights.
While single-purpose distribution analytics evolve to benefit department decision-making separately, they create countless cross-department frustrations later. Siloed analysis may arrive at an appropriate decision, but getting subsequent cross-department buy-in can ruin ROI because reaching a consensus takes so long.
Picture this:
Your inventory team makes a crucial decision in isolation using tools other departments can't access or don't fully understand. While that decision may positively optimize inventory investment, it also impacts sales, finance, business development, and more. Without full transparency, those other departments put up a wall of resistance until they grasp the basis for the decision and how they will be affected. Thus, an isolated approach makes it challenging for departments to get on the same page.
The result? Getting expected results may take twice as long because your teams are battling one another. The lack of company-wide transparency causes uncertainty, giving rise to negativity and pushback while leading to a string of pointless meetings that waste time and harm productivity. This familiar cycle can ruin the ROI of otherwise valuable analytics initiatives.
Siloed analytics and decision-making can affect your business in many ways. An essential first step is understanding the root cause of interdepartmental conflict resulting from siloed, single-function solutions.
Developing a Multi-Function Solution to Overcome Frustrations
One key thing a distributor can do to foster analytics alignment is to "connect" (though not necessarily integrate) multiple, single-purpose systems that don't natively interface with one another. A more transparent and inclusive approach can prevent analytics misalignment, improve company-wide adoption, and reinforce ongoing analytics success.
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Step 1: Develop a Larger Benchmarking Framework
A more comprehensive benchmarking or stratification framework improves analytics accessibility between every department and creates tie-ins between tools. It removes uncertainty by preemptively showing the inter-departmental impact of decisions, providing evidence that every department's needs and concerns have been considered. A common framework keeps the peace and improves buy-in.
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Step 2: Provide Full Transparency
The best overarching frameworks create full transparency, and distributors can benefit even further by clarifying every department's role in each analytics project. Full transparency breaks down conventional silos, allowing teams to work together instead of against one another.
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Step 3: Create Playbooks for Sustainable Improvements
Once a broader analytics framework is in place, developing step-by-step playbooks that outline and integrate day-to-day analytics decision-making will reinforce sustainable performance improvement. Playbooks establish repeatable workflows and routines, ensuring that successes continue beyond one-off wins.
Step 4: Provide Training and Education
As suggested previously, to ensure that all teams are on the same page, deploy your analytics solutions with ample training and education. In addition to improving adoption, it boosts transparency and reinforces your recipe for success.
Overcoming Classic Analytics Hurdles to Drive Success into 2024
Distribution analytics can take your business to new heights of success, but the three hurdles we've addressed threaten to make things far more complex and frustrating than necessary. Analytics should enhance your daily operations and support more extensive decision-making. However, overwhelming AI implementation choices, the intimidating cost of investing in a dedicated analytics team, and the potential time leakage from siloed decision-making stand in the way.
Fortunately, there are ways to overcome these hurdles and utilize analytics to your advantage. At ACTvantage, we provide plug-and-play solutions to help you drive profitable growth through analytics by offering modular tools, full transparency, and use-case-driven workflow training.
Our tools and dashboards can plug into your existing systems while introducing common frameworks and playbooks for use across departments. We provide training to improve adoption and foster ongoing routines and "habit-stacking" that trigger performance improvements that compound over time. ACTvantage helps you develop analytics capabilities in sales, inventory, pricing, and supply chain management, supporting your top and bottom lines.
With our Analytics-to-Action™, you can feel more confident harnessing AI-driven analytics, avoid excessive investments in internal analytics resources, and foster greater alignment in decision-making across departments. To leverage analytics that drive your business forward, contact us at ACTvantage today. We're ready to help you overcome these common hurdles and provide a solution that works.