- 8 minutes ago
As Malaysian manufacturers plan their 2027 investment budgets, the case for AI in manufacturing has to be feasible.
A faster production line may do little for margins, if orders are still held up by material shortages or cash is tied up in stock.
On NIAGA SPOTLIGHT, Tehmina Kaoosji speaks with Ben Lim, Regional Director, Sales for Malaysia & Singapore Territory at Epicor, about how manufacturers can pinpoint where margins are slipping and decide whether AI can improve production planning, reduce waste or help them deliver on time.
A faster production line may do little for margins, if orders are still held up by material shortages or cash is tied up in stock.
On NIAGA SPOTLIGHT, Tehmina Kaoosji speaks with Ben Lim, Regional Director, Sales for Malaysia & Singapore Territory at Epicor, about how manufacturers can pinpoint where margins are slipping and decide whether AI can improve production planning, reduce waste or help them deliver on time.
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NewsTranscript
00:07Hello, I'm Tamina Khosji and this is Nyaga Spotlight. Today our Spotlight falls on AI
00:12adoption in manufacturing. Now a factory can be busy carrying a full order book and still see
00:17its margins shrink with every new order it accepts. Malaysia's manufacturing capacity
00:23utilization has reached a very credible 83.7% in Q2 of 2026. Yet at the same time weak demand,
00:35material shortages and equipment maintenance continue to prevent manufacturers from operating
00:40at their full potential. Meanwhile Budget 2027 provides 30 million ringgit through MDEC to help
00:4744,000 MSMEs adopt AI and automation. So in this case, what should a manufacturer be looking at
00:56fixing first and foremost? Ben Lim, Regional Director for Sales for Malaysia and Singapore
01:03Territory at Epicor joins us now online to examine how manufacturers can price orders accurately,
01:10manage inventory without straining cash flow and decide whether the next investment should be in
01:15technology, machinery or bretta production planning for Q1 in 2027. A very good morning to you Ben.
01:23Thank you so much for making time to join us here on Nyaga Spotlight. How are you doing?
01:28Yeah, I'm doing fine. Good morning and thank you for of course having me here.
01:33Fantastic. So Ben, let's get straight into it and looking at where exactly manufacturers are losing
01:38money without really seeing it, given of course the expertise that Epicor has in this arena.
01:44Now, FMM, the Federation of Malaysian Manufacturing, their latest business survey, it identifies higher
01:50input costs and difficulty passing those costs to customers among manufacturers' concerns.
01:56From your work with Malaysian factories, which losses are being viewed as hardest for management to
02:02actually identify? Are we looking more at material waste? Are we looking at production delays? Or is
02:09there a cost of serving specific types of customers or industries? Tell us a little bit more about this arena.
02:18First of all, thank you for having me here again. I guess that is a very good question to start
02:23with.
02:24Um, be it SME or large local companies or even NNC. Um, these are very good questions to start with
02:32where they
02:33should be looking at what are the things that make them losing money day, in hours or in minutes. Yeah.
02:40So in, you know, cases, uh, no doubt, but big, big companies have big investments, small companies have limited
02:47funds, but these challenges still persist. Yeah. So the thing that they should ask themselves,
02:54is looking or trying to identify what are the small or repeated losses that, you know, really quietly
03:00erode the margins. As you know, you know, the cost is getting higher and higher, uh, for a lot of
03:06industry, uh, there's unavoidable, uh, for them to, you know, skip, uh, for example, tariffs, geopolitical
03:13issue, right? Supply chain disruptions. These are basically increasing costs for every manufacturers,
03:19be it here or overseas. Yeah. So it's important for them to identify these, uh, small repeated losses.
03:25Like what you have mentioned, uh, is actually aligned with, uh, uh, these sort of repeated losses
03:29and small hidden causes like, uh, small scrap wastage, or even that cause a lot of rework that
03:37have to be in place, yeah, to fulfill certain orders. And of course, if you look at, um, uh, the
03:44production side, this sort of downtime that is, uh, unexpected really also causing or erode the
03:50margins, yeah, for, uh, these sort of manufacturers and followed by once downtime is that happens or
03:57in terms of a schedule being disrupted, then it basically give a change impact towards, uh,
04:02overtime required. Yeah. And of course, uh, nevertheless,
04:07if a certain schedule of productions was disrupted, some stock was being kept, you know, for longer
04:13time period of time. So that, that is basically, um, so-called small and repeated losses that happening
04:20every day, every means at every minutes, every hour in manufacturers that are basically erode the margins.
04:26And if they would, manufacturers were able to identify these sort of small, uh, losses, yeah,
04:33it helps to increase their profit margins. And of course, nevertheless, uh, uh, helping them in terms
04:40of, uh, identify what is actually losing money. And to do this, I guess, manufacturers, uh, to be able
04:48to identify what I'm trying to say is, uh, they must have, of course, a platform that connect the
04:53informations from the sales orders, the productions, and then down to the finance or even the logistic,
04:59right. That only be able to help them, to give them a full picture of, uh, you know, where, uh,
05:06do I see the challenges is where do I see, you know, which small things is, uh, you know, uh,
05:12losing
05:12my money. And that is how you can identify and then put the right, you know, uh, in terms of
05:18solutions
05:19to, uh, handle it. But apart from just looking at solutions, you also need to be able to measure,
05:26you know, um, in these, uh, these challenges. First of all, I think it's important for you to
05:31identify the small losses and then down the road, you need to identify what is the true cause of
05:35fulfilling each order. Yeah. And putting this example, actually, it's a good thing that aligned
05:42to some of our customers in Africa. Uh, one reason customers that go live, uh, it's a local brand
05:48in Malaysia that, uh, a big brand that you will see them in every of the food chain. Excuse me.
05:55They basically manufactured the kitchen equipment where, right? So for them, they, they basically have,
06:03uh, of course, kinetic solutions that connect the informations from their sales order,
06:07right down to the, uh, shipment. So these give them a full visibility to the system in terms of
06:14if proof, uh, efficiency on those, uh, costs that is not accurate at the first place. Yeah.
06:21And when they are being able to nail down to those costs accurately, they are able to, uh, in a
06:27way,
06:27improve their, uh, margin profit margin. Um, that is one, one of the example that I can pull off that
06:36how in practical way, uh, you know, I can advise how customers can, you know, identify this sort of
06:42losing money and of course, increase the profit margin. But overall, I guess it's important before
06:48the next big investment is, it's important to understand where, uh, you're losing money today,
06:54you know, uh, of course, before, you know, putting up the next investment.
06:59Thank you. Thank you very much, Ben, for that really good, um, overview,
07:02because also the Federation of Malaysian Manufacturing, they did conduct a survey with
07:06close to 700 manufacturers. And what they found out was close to 70% of them are actually really
07:11reporting higher production costs and all the tips as well as insights that you've shared with us,
07:17hopefully helps to, um, look out for those, um, small daily factors and expenses that actually
07:24add up and ultimately will be cutting down on profit margins, regardless of whether or not a
07:29factory is actually busy all the time, because that can actually be deceptive. So let's move on from
07:35there, Ben, and looking at, um, factory floors themselves. And of course, about the big question
07:41about whether a different production plan is required, or is it actually about upgrading, uh,
07:46machines? Now, DOSIM, the Department of Statistics, Malaysia, has identified, uh, weak demand,
07:53material shortages, and also machinery maintenance, among the reasons our factories operate a little
08:00below capacity. Now, um, each of these factors, it requires a really different response, uh, before
08:06a manufacturer, let's say, buys equipment or automates a production line, what is important for them
08:12to establish, uh, when it comes to the factors limiting their output? Tell us a little more about
08:19these finer details. Excuse me. Sorry for my intro. So, uh, very good question to start with, um, and, uh,
08:31manufacturers in Malaysia, uh, in a lot of cases, they always thought that, you know, throwing a big
08:37investment on another machine basically, you know, give me more productivity, uh, capacity. Yeah.
08:43Serve more customers. I can get more orders. Right. Um, but they never thought of, uh, in a lot of
08:49cases, I won't say they never, but in a lot of cases, manufacturers, uh, kind of undermined questions
08:54of where is my bottleneck in the production line? Right. Is it, uh, due to certain bookshop,
09:00certain machines, yeah, old machines, uh, or due to the process is not so, uh, connected seamlessly
09:08that basically creates a bottleneck or even the operators is not, uh, up to skill to operate
09:14certain machines. Yeah. And you rely very much on limited resources. So these are things that, uh,
09:18we should look at, should be asking, manufacturers should be asking themselves, where is my bottlenecks?
09:23Yeah. So in terms of the bottlenecks, that means manufacturers should look at, identify,
09:28or find the constraints or limitations that you mentioned. Yeah. Uh, be it, is it, you know,
09:34the demand is a sudden spike. Yeah. Maybe due to sudden spike and it doesn't manage for longer term.
09:40And, uh, do you have a shortage of, uh, materials all the time or do your suppliers of your materials,
09:46uh, have this, uh, delivery issue all the time? Yeah. Delayed delivery to use, or you may have always
09:53really under, you know, uh, buffer in terms of your safety stock, right? Important SKU, you always buffer,
10:00you usually have a buffer, which is across the board. Then, um, one very important
10:07elements, which is, uh, a lot of manufacturers also miss out is, uh, of course due to, uh, they don't
10:13have a seamless information across the whole organizations. Maintenance is one key thing that
10:20they always neglect. Yeah. They may do it manually and it is not seamlessly integrated to the, uh,
10:27scheduling or production planning. So they may accidentally, or, you know, uh, schedule some
10:33maintenance during a particular important job that basically, you know, uh, whole productions,
10:39if that is being executed at the middle of your production, right? That also links back to the
10:45scheduling, scheduling constraints, right? So, uh, if we look back at all these elements, uh,
10:51kickstart with, uh, materials there, which is, won't say the easiest to, to, um, counter, but, um,
10:57it is actually one thing that a lot of manufacturers care the most. So you're right. Make materials
11:03available before job starts. That's the most, you know, simple thing, right? Simple to say, but always is,
11:08uh, do you have that kind of a capability or visibility to do that kind of planning? Yeah. Buyer have
11:14been always buying stuff, but they always made or accidentally, uh, you know, overlook certain
11:21materials that should have more buffer down the road because there's a history of telling us that,
11:27for example, our sales order for certain seasonal greetings is coming and you know, the spike of the
11:32demand will be high, but then you didn't react towards it, right? You do have that data, but you
11:37didn't react to it, right? Then, um, another part that we should look at for manufacturers, definitely
11:43where she said how you can improve your scheduling, your schedules of job. And of course, how you
11:48schedule it to optimize your machines. Yeah. And then with that capability of planning and scheduling
11:56integrated across your machine's availability, that is so important to help manufacturers to be
12:02able to plan and maintenance around the production job order rather than during some important productions
12:10is happening, right? Of course, you can prioritize since you have the information of, you know, your
12:16sales order, your job, what you have planned and availability of your machines. With that visibility,
12:21you can plan. Yeah. You can prioritize what, you know, due to depends on the delivery day, depends on
12:26the price that customers or customers, you can plan accordingly. Then it was only fit in your maintenance
12:32either, not always later after important deal, but it may be earlier, right? Because earlier prevents
12:40sudden, uh, these are down time that is so important for you to make sure that your production's
12:46being optimized. Yeah. If you would be able to tackle one or two rounds of downtime, sudden shock
12:52to your production line in a year, that basically telling you that you are freeing up a lot of capacity
12:57for your production plan. So again, I say, um, I think it's also, uh, to our manufacturers to, to do
13:04these
13:04steps, um, basically you need to be able to measure what is the good output, right? Set, uh, basically a
13:11baseline
13:11one is before you try to improve your better production plan. And then after the solutions
13:19being, uh, implement or technology being introduced after implementation, what is the comparison? Do you, uh,
13:27still optimize your production shop floor? Is your machine always still out of, uh, uh, uh, sorry, optimize
13:36your utilization on a hundred percent utilization? That, that is a good, good thing for you, right?
13:41If after you compare and did this sort of, uh, groundwork, that gives you a stronger business
13:45case for you to invest the next machine, the next technology. But before you jump into the gun and
13:51straight away, you know, invest a big, big machine. Those are some great insights over there, Ben,
13:56because actually it will be more about having an overall view rather than just pushing ahead to get
14:02more equipment before actually streamlining completely those workloads. Thank you for the
14:06insights so far. We do take a quick break now. Don't go anywhere. We'll be back with the rest of
14:10this
14:10conversation only on Nyaga Spotlight. Welcome back to Nyaga Spotlight, still with me Tamina Kalsri.
14:31And today we're focusing on all things AI adoption and manufacturing with Ben Lim of Epicor joining us
14:36online for this very important discussion. So Ben launching straight back into the conversation and
14:42looking at how much inventory businesses can actually afford to hold. You'd made a very good
14:47point earlier about the fact that most businesses that are in the manufacturing sector, they do, um,
14:52understand the seasonal demand, but sometimes manufacturers, they face a little bit of unreliable
14:57deliveries, um, around these, uh, particular seasons. So they may actually be buying extra materials to
15:03protect production, even as customers become a little less predictable about orders. Um, how
15:09should purchasing and production teams then decide which materials justify a buffer and which are tying
15:16up, um, cash flows unnecessarily? Tell us a little more on this. All right. Um, I guess it's important
15:24questions for manufacturers, again, especially for buyers, yeah, and our planners. I, well, we always love to
15:31have the answer straight answer, you know, how much, uh, but it is actually, there's no, uh, definite
15:37answer, uh, but the, the philosophy of, uh, making this a right is the right stock, uh, that protects
15:44product productions and your cashflow. That would that means the right inventory for you to, to afford or
15:50hope. And in a lot of cases, uh, to do this, you manufacturers definitely need to, you know, assess
15:57each material, uh, critically, right? You don't basically have the same planning, right? Same buffer
16:04across the board for each of your material. Then basically you're trying to create a risk for by
16:09yourself, not by suppliers. And then of course, uh, when it comes to each category or each individually
16:16important parts that you have material, uh, do assess the supplier risk. Yeah. Is it from certain region that,
16:24you know, may be exposed to a potential of, uh, disruption? Yeah. And, uh, it's best is always
16:31to substitute with a supplier, uh, from different region. And of course, look at also the demand trend.
16:38Yeah. Uh, like I shared with you just now, uh, seasonal greetings, of course, uh, do have a spike
16:43on certain, uh, products, certain, to certain industry. And then first, uh, one or two months
16:49before you always should have these, uh, uh, buffer being taken care. And of course, um, I guess it's
16:56important for you to keep a buffer where a shortage can really cause a production stop, right? That is
17:13also important to review orders, um, the stocks and, uh, incoming deliveries as forecast changes,
17:20right? Set a periodically, uh, preview required by either materials group. Yeah. We can't always
17:27review everything, you know, across the board on certain time, but I guess it's very important for
17:32to be able to set a periodic review on my group on, uh, uh, each time so that your forecast,
17:38uh, very well,
17:41uh, uh, introducing the right data for you to, you know, basically order the right buffer for
17:47your safety stock level. And again, uh, every ringgit unnecessary, you know, being tied up in
17:52the stock is, uh, basically unavailable elsewhere in your organization. So it's important to look at
17:57this. Uh, I think this question is very good. Clearly. And of course, um, for every year's planning.
18:03So now we move on into looking at, uh, urgent orders. Now, urgent orders can, of course,
18:08earn useful revenue, particularly during peak seasons, but it also done does require overtime,
18:14expensive freight, or even changes that can delay other customers download downstream. So what should
18:19a manufacturer know before they go ahead and promise a price and delivery date? And how should the
18:25calculation differ in case the factory has spare capacity versus when accepting the order would
18:31actually displace other ongoing orders or work?
18:37These pop up, uh, to, uh, many organizations of manufacturers a lot of time. Yeah. Uh,
18:44be it disruptions elsewhere, that means a potential opportunity to our region, uh, manufacturers.
18:49So on and off, there's this urgent order pops up to an organizations or manufacturers,
18:54and that is a question station, you know, ask themselves. Yeah. Does this order really improve
19:00the business after its full impact? Yeah. So maybe we unfold a little bit over what we mean by
19:05full impact. Um, definitely they have to encounters, sorry, they have to include, uh,
19:13the, this, uh, strongly analyze. Is it any overtime required for me to accept this order? Firstly,
19:21yeah, do I have the buffer capacity to take up this? Am I able to reprioritize my production plan? If
19:30I
19:30were to take up this order, would this disrupt my production setup? Right? Urgent order may comes in
19:37all of a sudden and you're trying to fulfill, you know, being a very loyal suppliers, you're trying to
19:42fulfill your customers and it will disrupt straight away. What is your job now? And you try to shift your
19:46setup. That really costs you a lot. And then followed by materials, right? If you disrupt
19:51your production plan or job order scheduling, that also in a chain impact to your material,
19:58you know, availability for this urgent order and the following orders, right? If this happens to your
20:04inventory again, do you have a sufficient buffer? Then followed by, if not sufficient,
20:09the urgent freight that you, uh, in, in, in terms to, uh, sorry, that you intend to order,
20:16or that increase your costs. So this really needs a lot of, uh, uh, informations across integrated
20:24across your organizations to be able to answer these sort of questions. So when you look at the
20:29spare capacity, definitely you have to, uh, like I mentioned just now, you have to access additional
20:35costs. And would this contribute more revenue rather than contributing more cost to you, right? And
20:41basically spike up the costs rather than increase the margin. So this is a good question. If you're
20:47able to answer yourself, it will assist you to really, yes, I have the spare capacity, but it
20:54will increase my costs. So the questions now is that, do you want to have a different pricing for this
21:01urgent order? Right? So we are, while you still maintain your margin. So it's always best that you can
21:07have full capacity across your production line, right? Uh, but definitely you have to include
21:11this space, you know, order that the chain impact order. Yeah. The next order. And, uh, definitely
21:17you have to be able to answer or reprioritize with your other orders or your other customers, right?
21:24If again, if you have that information that basically gives you more confidence to, uh,
21:29take up this urgent order, right? I think, uh, that will be some of my advice. Also like late delivery
21:36margins, for example, can actually completely erase any kind of additional profit that you may be
21:42getting in. Um, so that brings us to a very crucial area as well, Ben. And, um, where does AI
21:48improve
21:49any manufacturing decisions in your experience? Now, um, manufacturers have been using general AI
21:55tools and is much more widespread than deeper factory transformations. Uh, let's look at, um,
22:01operational decisions. Uh, there's, you know, forecasting demands, scheduling production,
22:05or even identifying a quality problem. Tell us a little more about where AI can improve on existing
22:11methods and what information is required and how should a manufacturer be able to test the
22:17recommendations from AI systems before relying on them?
22:24Yeah. It's a, it's a very great hype as you know, AI in a bucket. Uh, yeah. And I want
22:31to mention
22:31just, uh, generative AI, generic AI for across the board, uh, for every organization to apply. But
22:37when it comes to Epicor, we focus very much on AI that assists or infuse into enterprise platform that
22:43assists straight away to our manufacturers that we serve. I think, uh, when we are looking at AI,
22:49don't look as, you know, a bandwagon to jump in straight away. Yeah. Invest in new technology.
22:56Don't have that kind of mentality. I always advise my manufacturers, my, my fellow customers to start
23:02with your business problem. Yeah. Don't start with more G the other way around. If you are able to be
23:08very clear and after identifying your business problem, yeah, this is the key part before choosing any AI.
23:16So for example, you mentioned about demand forecasting. Yeah. That's a good example,
23:20a very practical one. Yeah. Um, AI in this area really can analyze the sales history
23:28and current orders that you're about to simulate in that, uh, the demand forecasting system, right?
23:35AI gives you all these algorithms, uh, based on certain, uh, this, uh, concept algorithm that they can
23:44help to plan production and purchasing, um, and you can simulate, excuse me, and you can simulate the
23:50situations based on certain algorithm, um, then decide, uh, based on the suggestions from this
23:56demand forecasting. Um, having said that you definitely need the data to be input to this sort of, uh,
24:04you know, AI assisted demand forecasting, right? Data quality matters. So in this case, make sure that,
24:09you know, data is complete and consistent so that it doesn't mislead your forecast suggestion, right?
24:15That's also very important. Apart from knowing that, oh, I have a very good, good technology, but
24:20you know, while deploying, you definitely have to go into these sort of elements. Um, start small, um,
24:26always you can, uh, identify. Oh, for my customers, they may identify, let's say eight to nine,
24:32you know, these sort of, uh, problems that they are facing, but you can always start small,
24:36as in phase accordingly, which are your priority of what are the, uh, problems that you are trying
24:42to tackle and measure the results. Again, it comes back to what I mentioned just now, you have to set
24:47out a baseline, how you measure the, uh, improvement after undertaking this, uh, AI, uh, technology,
24:54uh, deploying to certain of your process, then keeping people accountable. Yeah. People always
24:59thought that, oh, AI comes in there, we replace resources, replace employees. I, I, I don't think
25:04that we honestly, we have, we have about, uh, globally, uh, about more than a hundred,
25:09a hundred customers that has deployed our ethical prism of AI infused to our solutions.
25:14And now we are not reducing their employees, but instead we are empowering the employees to
25:19basically do a lot of more automations to the identified problems. Yeah. Make sure they have more
25:26times to validate the data is complete and consistent, right. Then give them better decision faster.
25:33So these are the things that I really assist, uh, our people doing more with AI. And of
25:41course, uh, keep it proportionate, stable, uh, predictable demand may only require simple
25:47matter. What does it mean? Sometimes you don't try to complicate a problem, right? It is a single
25:53problem. Just probably put up a simple, uh, you know, automations to it. Don't really complicate,
25:59try to leverage every AI everywhere possible, right? But just keep it, uh, at some point,
26:05keep it simple. So, um, for Malaysian manufacturers, uh, I think the questions for this, uh, AI
26:11topic, uh, you should ask is where can AI help us make a better business decision? And can we measure
26:19the improvement? That is also key. Absolutely. And there's plenty of room for actually more AI
26:25adoption because Federation of Malaysian manufacturers, their data is showing that
26:29less than 40% of our SMEs and MSMEs, et cetera, are actually using, um, industry 4.0 style AI
26:38to streamline their manufacturing processes. Um, so Ben, as we close out and land the discussion,
26:44um, some quick thoughts on, um, as manufacturers plan their 2027 spending after budget tabling,
26:50tell us about, um, what can be done now so that, um, all the manufacturing businesses out there,
26:57they are able to perhaps, um, work with one improvement that comes with AI adoption
27:03without having to committing to a factory-wide overall.
27:10Yeah. I think, uh, for manufacturers, there's like, like I always share, it's very important.
27:17Uh, I mean, conceptually, you are very, very important and look at, uh, these sort of deployments
27:22to improve your productivity, improve your efficiency. Don't start big bang, right? Don't go and
27:29consider, uh, once you identify all your problems, don't go and consider to deploy everything at one
27:34shot, right? Uh, big bang approach, but you should be able to, uh, pick one costly, prioritize it,
27:40costly problem, prioritize it, establish, uh, what is the cost, uh, the business today and set a very
27:46clear target for this improvement when you solve this problem and do agree success measure with the
27:53team, right? Top management itself knowing that, you know, the success measure is not important, but
27:59the message has to basically, uh, the goal or the success measurement has to be transpired across the
28:04team very clearly so that everyone record the baseline. And as well, at the same time, after pilots are
28:10done, will they be able to review this in stages together and then compare again, the similar
28:18runs that account for extra, is it really require extra demand or support, right? Sometimes we see
28:24that, oh, why can I deploy certain automations? I saw my revenue goes up, but do your increase of
28:30revenue goes up due to you have more demand and you require more support, you've got more OT, you have
28:36more
28:36material, then that is the by right, the revenue should go up, right? But you should be looking at
28:41the baseline that you said, if I were to have the same resources, same material, same, uh, shift required
28:48to operate this job, do I increase my revenue? So if yes, that is increased that proof, basically you already,
28:58uh, have enjoyed the value of this, uh, uh, uh, AI deployment or automation deployment across, uh,
29:06and you're ready to basically deploy it more. But if let's say, uh, you think that, oh, the measurement
29:12of the success is just so-so, uh, then you actually not to stop, but in fact, you should review
29:19again,
29:19where the wind goes wrong, right? Because the problem is still there. Yeah. But you still need
29:24to find a way. Ben, thank you very much for the discussion so far and also for sharing some
29:28top tips for, uh, manufacturers going ahead, uh, beyond Q4 of 2026 and moving into Q1 of 2027.
29:36We really appreciate your insights. So everyone, that was Ben Lim, of course, um, Regional Director
29:41of Sales for Malaysia and Singapore Territory at Epicor. Now for manufacturers, growth depends on
29:47knowing where value is being lost and which investment will deliver a measurable return.
29:51That's exactly how businesses can strengthen margins without placing unnecessary pressure on cash flow.
29:57That's all we have time for today on Niagara Spotlight. I'm Tamina Khosji signing off for now.
30:02Here's to a productive week ahead.